{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Output/Committee Delay.MANUSCRIPT RESULTS.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}29 Dec 2024, 23:15:11
{txt}
{com}. 
.   
.   
. **** JSB UPDATED DATABASE: ADDING EXECUTIVE NOMINATION POSITIONS COVERED IN OSTRANDER DATABASE FROM MAY 2012 THROUGH DECEMBER 2020 AND UPDATING ALL OTHER DATA [SUMMER\FALL 2023]: /// 
> *** ADDITIONAL VARIABLES ADDED IN MARCH 2024 IN RESPSONSE TO LSQ REFEREE REPORTS ****
. 
. 
. 
. **** "EXECUTIVE DEFERENCE OR LEGISLATIVE CONSTRAINT? COMMITTEE FOUNDATIONS OF CONFIRMATION DELAY FOR U.S. EXECUTIVE BRANCH APPOINTMENTS" [KRAUSE & BYERS] ****
. 
.  
. 
.    
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
.    
.    
.  
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. *** DEPENDENT VARIABLE:         legvet2 / legvetdur2plus1 = legvet2+1 [ENSURE NONZERO VALUES FOR DURATION OUTCOME VARIABLE]
. 
. 
. 
. 
. *** PRIMARY COVARIATES/MODELS:  MODEL 1 [COX]:  committee_pres1  sendivide  committee_pres1 * sendivide  [CONTROLS, PLUS COMMITTEE & PRESIDENTIAL ADMINISTRATION UNIT EFFECTS]                             
.                  
. ***                             MODEL 2 [COX]:  chair_pres1  sendivide   chair_pres1 * sendivide  [CONTROLS, PLUS COMMITTEE & PRESIDENTIAL ADMINISTRATION UNIT EFFECTS]    
. 
. ***                             MODEL 3 [WEIBULL]:  committee_pres1  sendivide  committee_pres1 * sendivide  [CONTROLS, PLUS COMMITTEE & PRESIDENTIAL ADMINISTRATION UNIT EFFECTS]          
.              
. ***                             MODEL 4 [WEIBULL]:  chair_pres1  sendivide   chair_pres1 * sendivide  [CONTROLS, PLUS COMMITTEE & PRESIDENTIAL ADMINISTRATION UNIT EFFECTS] 
. 
. 
. **************************************************************************************************************************************************************************************** **************************************************************************************************************************************************************************************** *************************************************************************************************************************************************************************************** ****************************************************************************************************************************************************************************************
.                                                   
.                           
.   
. *** COMMITTEE CONTROL COVARIATES:       experience_median [MODELS 1 & 3] / chair_experience_1 [MODELS 2 & 4]; ///
> ***                                                                             ln_combills_workload; committeestaffsize [# Committee Staff]   
.     
. *** OSTRANDER CONTROL COVARIATES:       sendivide  polarization pres_app_m first90 preselection lameduck workload [Executive Civilian Nominations: Senate] 
. ***                                                                             female priorconfirm _Itier_2 _Itier_3 _Itier_4 defense infrastructure social
. 
. 
. *** ADDITIONAL CONTROL COVARIATES:      pressenfloorabsdist [-] [|Senate Floor Median - President|]; kv_workload (# civilian executive nominations made in a given year/session)        
. ***                                                                             denied [-] [nominee previously denied in same Congress]; fvra [+] [= 1 if subject to FVRA 1998, = 0 otherwise]; 
. ***                                                                             firstrecess[-] [= 1 is nominated in July or August affected by August Recess, = 0 otherwise]; 
. ***                                                                     secondrecess [-] [= 1 is nominated in November or December affected by December Recess, = 0 otherwise]; major policy agency binary indicator [-];                      
. ***                                     committee-level & pressidential administration unit/fixed effects.
.                                         
.                                 
.                                                         
.  
.  
.    ******  NOTE: PRIVIELGED NOMINATIONS (N = 244) ARE EXCLUDED SINCE THEY BYPASS THE NORMAL SENATE CONFIRMATION PROCESS [INCLUDING COMMITTEE VETTING] -- 
.    ******        THESE APPEAR AS MISSING VALUES FOR "legvet2" COMMITTEE CONFIRMATION DURATION VARIABLE
. 
. 
.    ******       [UNCENSORED SUBSAMPLE==CONFIRMED IN CURRENT CONGRESS: N = 7,076 [71.63%] + CENSORED SUBSAMPLE==UNCONFIRMED IN CURRENT CONGRESS: N = 2,803 [28.37%] 
.    ******       TOTAL EFFECTIVE SAMPLE = 9,879] **** 
.    
.            
.            
.            
.            
.            
.            
.            
. **** ESTIMATION STRATEGY: COX SEMIPARAMETIC REGRESSION [NONPARAMETRIC HAZARD] ****         
.            
.            
.            
.            
.            
.            
.            
.   
.  * OPEN UPDATED "CONFIRMATION DELAY & SENATE COMMITTEES PROJECT" BASE DATABASE [12-17-2024] *
.  
.  
. *use "C:\Users\gk57526\Dropbox\Confirmation Dynamics Project (Jason Byers)\Confirmation Delay & Senate Committees\2023 Version\Fall 2024\Statistics\Data\Krause and Byers Data (12.17.2024).dta", replace
. 
. use "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Data/Krause and Byers Data (12.17.2024).dta", replace
{txt}
{com}. 
. 
. 
. ***************************************************************************************************************************
. 
. encode agency, generate(agency_id)
{txt}
{com}. 
. 
. 
. **** CREATE MAJOR POLICY AGENCY BINARY INDICATOR [= 1 FOR MAJOR POLICY-RELATED AGENCIES; = 0 OTHERWISE -- E.G., MINOR COMMISSIONS, COUNCILS, ADVISORY GROUPS, ETC......]
. 
.  
. generate policy_majagency = 1 if agency_id>=1 & agency_id<=2 | agency_id==5 | agency_id==12 | agency_id>=32 & agency_id<=34 | agency_id>=36 & agency_id<=39 | agency_id==41 | agency_id>=43 & agency_id<=45 | agency_id>=50 & agency_id<=51 | agency_id==54 | agency_id >=57 & agency_id<=59 | agency_id==62 | agency_id>=64 & agency_id<=83 | agency_id>=85 & agency_id<=87 | agency_id>=90 & agency_id<=94 | agency_id==96 | agency_id>=98 & agency_id<=104 | agency_id>=106 & agency_id<=107 | agency_id>=110 & agency_id<=112 |  agency_id>=114 & agency_id<=127 | agency_id>=130 & agency_id<=131 | agency_id==136 | agency_id>=146 & agency_id<=148 | agency_id>=150 & agency_id<=152 | agency_id==155 | agency_id>=167 & agency_id<=168 | agency_id==186 | agency_id>=194 & agency_id<=195 | agency_id>=199 & agency_id<=203 | agency_id==205 | agency_id>=208 & agency_id<=222 | agency_id>=226 & agency_id<=227 |agency_id==232 | agency_id>=234 & agency_id<=235 | agency_id>=245 & agency_id<=246 | agency_id>=253 | agency_id==255 | agency_id==260 | agency_id==269 | agency_id==271 | agency_id==274|  agency_id>=277 & agency_id<=279
{txt}(2,718 missing values generated)

{com}. *
. replace policy_majagency = 0 if policy_majagency==.
{txt}(2,718 real changes made)

{com}. 
. ******************************************************************************************************************************************************************************************************************************************************
. 
. *FIGURES 1 & 2*
. 
. generate legvetdur2plus1 = legvet2+1
{txt}(244 missing values generated)

{com}. 
. stset legvetdur2plus1, failure(confirmbinary)

{txt}Survival-time data settings

{col 10}Failure event: {res}confirmbinary!=0 & confirmbinary<.
{col 1}{txt}Observed time interval: {res}(0, legvetdur2plus1]
{col 6}{txt}Exit on or before: {res}failure

{txt}{hline 74}
{res}     10,354{txt}  total observations
{res}        244{txt}  event time missing (legvetdur2plus1>=.){col 61}PROBABLE ERROR
{hline 74}
{res}     10,110{txt}  observations remaining, representing
{res}      7,166{txt}  failures in single-record/single-failure data
{res}    988,097{txt}  total analysis time at risk and under observation
                                                At risk from t = {res}        0
                                     {txt}Earliest observed entry t = {res}        0
                                          {txt}Last observed exit t = {res}      730
{txt}
{com}. 
. quietly streg   committee_pres1  chair_pres1     sendivide    kv_workload   chair_experience_1  committeestaffsize polarization pres_app_m first90 preselection lameduck workload  female priorconfirm x_itier_2 x_itier_3 x_itier_4 defense infrastructure social   experience_median  fvra firstrecess secondrecess policy_majagency ln_combills_workload i.kbcom_1, distribution(weibull) vce(cluster kbcom_1)
{txt}
{com}. 
. 
. 
. 
. *Figure 1 Boxplot (Overall)*
. 
. drop if kbcom_1 == 21
{txt}(421 observations deleted)

{com}. 
. graph hbox legvetdur2plus1 if e(sample), over(kbcom_1, relabel(1 "Agriculture, Nutrition, and Forestry" 2 "Armed Services" 3 "Banking, Housing, and Urban Affairs" 4 "Budget" 5 "Commerce, Science, and Transportation" 6 "Energy and Natural Resources" 7 "Environment and Public Works" 8 "Finance" 9 "Foreign Relations" 10 "Governmental Affairs" 11 "Health, Education, Labor, and Pensions" 12 "Homeland Security and Government Affairs" 13 "Indian Affairs" 14 "Intelligence" 15 "Judiciary" 16 "Labor and Human Resources" 17 "Rules and Administration" 18 "Small Business" 19 "Small Business and Entrepreneurship" 20 "Veterans' Affairs") label(labsize(small))) nooutside ///
> ylabel(0(50)500, nogrid labsize(small)) ///
> note("") ///
> ytitle("Duration of Committee Deliberation", size(small) margin(t=2)) ///
> title("FIGURE 1: Box-Whisker Plots of Committee" "Confirmation Delay by Senate Committee", size(small))
{res}{txt}
{com}. 
. graph save "Graph" "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure1.gph", replace
{res}{txt}file {bf:/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure1.gph} saved

{com}. 
. 
. 
. 
. 
. 
. 
. *Figure 2 Boxplot (Unified versus Divided Control of Executive Appointment Process) *
. 
. stset legvetdur2plus1, failure(confirmbinary)

{txt}Survival-time data settings

{col 10}Failure event: {res}confirmbinary!=0 & confirmbinary<.
{col 1}{txt}Observed time interval: {res}(0, legvetdur2plus1]
{col 6}{txt}Exit on or before: {res}failure

{txt}{hline 74}
{res}      9,933{txt}  total observations
{res}         54{txt}  event time missing (legvetdur2plus1>=.){col 61}PROBABLE ERROR
{hline 74}
{res}      9,879{txt}  observations remaining, representing
{res}      7,076{txt}  failures in single-record/single-failure data
{res}    987,811{txt}  total analysis time at risk and under observation
                                                At risk from t = {res}        0
                                     {txt}Earliest observed entry t = {res}        0
                                          {txt}Last observed exit t = {res}      730
{txt}
{com}. 
. quietly streg   committee_pres1  chair_pres1     sendivide    kv_workload   chair_experience_1  committeestaffsize polarization pres_app_m first90 preselection lameduck workload  female priorconfirm x_itier_2 x_itier_3 x_itier_4 defense infrastructure social   experience_median  fvra firstrecess secondrecess policy_majagency ln_combills_workload i.kbcom_1, distribution(weibull) vce(cluster kbcom_1)
{txt}
{com}. 
. 
. *figure 2 boxplot
. 
. *divided 
. gen dpg_min = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p1  = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p5  = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p10 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p25 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p50 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p75 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p90 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p95 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_p99 = .
{txt}(9,933 missing values generated)

{com}. gen dpg_max = .
{txt}(9,933 missing values generated)

{com}. 
. 
. *unified
. gen upg_min = .
{txt}(9,933 missing values generated)

{com}. gen upg_p1  = .
{txt}(9,933 missing values generated)

{com}. gen upg_p5  = .
{txt}(9,933 missing values generated)

{com}. gen upg_p10 = .
{txt}(9,933 missing values generated)

{com}. gen upg_p25 = .
{txt}(9,933 missing values generated)

{com}. gen upg_p50 = .
{txt}(9,933 missing values generated)

{com}. gen upg_p75 = .
{txt}(9,933 missing values generated)

{com}. gen upg_p90 = .
{txt}(9,933 missing values generated)

{com}. gen upg_p95 = .
{txt}(9,933 missing values generated)

{com}. gen upg_p99 = .
{txt}(9,933 missing values generated)

{com}. gen upg_max = .
{txt}(9,933 missing values generated)

{com}. 
. 
. *difference
. gen commdelay_dpc_upc_min = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p1 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p5 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p10 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p25 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p50 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p75 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p90 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p95 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_p99 = .
{txt}(9,933 missing values generated)

{com}. gen commdelay_dpc_upc_max = .
{txt}(9,933 missing values generated)

{com}. 
. 
. levelsof kbcom_1, local(committees)
{res}{txt}1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

{com}. 
. foreach c in `committees' {c -(}
{txt}  2{com}.         
.         *divided statistics
.     quietly summarize legvetdur2plus1 if e(sample) & sendivide == 1 & kbcom_1 == `c', detail
{txt}  3{com}.     replace dpg_min  = r(min)  if kbcom_1 == `c'
{txt}  4{com}.         replace dpg_p1   = r(p1)   if kbcom_1 == `c'
{txt}  5{com}.         replace dpg_p5   = r(p5)   if kbcom_1 == `c'
{txt}  6{com}.         replace dpg_p10  = r(p10)  if kbcom_1 == `c'
{txt}  7{com}.         replace dpg_p25  = r(p25)  if kbcom_1 == `c'
{txt}  8{com}.         replace dpg_p50  = r(p50)  if kbcom_1 == `c'
{txt}  9{com}.         replace dpg_p75  = r(p75)  if kbcom_1 == `c'
{txt} 10{com}.         replace dpg_p90  = r(p90)  if kbcom_1 == `c'
{txt} 11{com}.         replace dpg_p95  = r(p95)  if kbcom_1 == `c'
{txt} 12{com}.         replace dpg_p99  = r(p99)  if kbcom_1 == `c'
{txt} 13{com}.         replace dpg_max  = r(max)  if kbcom_1 == `c'
{txt} 14{com}.         
.         *unified statistics
.         quietly summarize legvetdur2plus1 if e(sample) & sendivide == 0 & kbcom_1 == `c', detail
{txt} 15{com}.     replace upg_min  = r(min)  if kbcom_1 == `c'
{txt} 16{com}.         replace upg_p1   = r(p1)   if kbcom_1 == `c'
{txt} 17{com}.         replace upg_p5   = r(p5)   if kbcom_1 == `c'
{txt} 18{com}.         replace upg_p10  = r(p10)  if kbcom_1 == `c'
{txt} 19{com}.         replace upg_p25  = r(p25)  if kbcom_1 == `c'
{txt} 20{com}.         replace upg_p50  = r(p50)  if kbcom_1 == `c'
{txt} 21{com}.         replace upg_p75  = r(p75)  if kbcom_1 == `c'
{txt} 22{com}.         replace upg_p90  = r(p90)  if kbcom_1 == `c'
{txt} 23{com}.         replace upg_p95  = r(p95)  if kbcom_1 == `c'
{txt} 24{com}.         replace upg_p99  = r(p99)  if kbcom_1 == `c'
{txt} 25{com}.         replace upg_max  = r(max)  if kbcom_1 == `c'
{txt} 26{com}.         
.         *committee difference
.         replace commdelay_dpc_upc_min = dpg_min - upg_min if kbcom_1 == `c'
{txt} 27{com}.         replace commdelay_dpc_upc_p1  = dpg_p1 - upg_p1   if kbcom_1 == `c'
{txt} 28{com}.         replace commdelay_dpc_upc_p5  = dpg_p5 - upg_p5   if kbcom_1 == `c'
{txt} 29{com}.         replace commdelay_dpc_upc_p10 = dpg_p10 - upg_p10 if kbcom_1 == `c'
{txt} 30{com}.         replace commdelay_dpc_upc_p25 = dpg_p25 - upg_p25 if kbcom_1 == `c'
{txt} 31{com}.         replace commdelay_dpc_upc_p50 = dpg_p50 - upg_p50 if kbcom_1 == `c'
{txt} 32{com}.         replace commdelay_dpc_upc_p75 = dpg_p75 - upg_p75 if kbcom_1 == `c'
{txt} 33{com}.         replace commdelay_dpc_upc_p90 = dpg_p90 - upg_p90 if kbcom_1 == `c'
{txt} 34{com}.         replace commdelay_dpc_upc_p95 = dpg_p95 - upg_p95 if kbcom_1 == `c'
{txt} 35{com}.         replace commdelay_dpc_upc_p99 = dpg_p99 - upg_p99 if kbcom_1 == `c'
{txt} 36{com}.         replace commdelay_dpc_upc_max = dpg_max - upg_max if kbcom_1 == `c'
{txt} 37{com}.         
. {c )-}
{txt}(307 real changes made)
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{com}. 
. duplicates drop kbcom_1, force

{p 0 4}{txt}Duplicates in terms of {res} kbcom_1{p_end}

{txt}(9,913 observations deleted)

{com}. 
. reshape long commdelay_dpc_upc_, i(kbcom_1)  j(statistic min p1 p5 p10 p25 p50 p75 p90 p95 p99 max)

{txt}Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}          20   {txt}->   {res}220         
{txt}Number of variables        {res}         121   {txt}->   {res}112         
{txt}j variable (11 values)                    ->   {res}statistic
{txt}xij variables:
{res}commdelay_dpc_upc_min commdelay_dpc_upc_p1 ... commdelay_dpc_upc_max{txt}->{res}commdelay_dpc_upc_
{txt}{hline 77}

{com}. 
. 
. graph hbox commdelay_dpc_upc_, over(kbcom_1, relabel(1 "Agriculture, Nutrition, and Forestry" 2 "Armed Services" 3 "Banking, Housing, and Urban Affairs" 4 "Budget" 5 "Commerce, Science, and Transportation" 6 "Energy and Natural Resources" 7 "Environment and Public Works" 8 "Finance" 9 "Foreign Relations" 10 "Governmental Affairs" 11 "Health, Education, Labor, and Pensions" 12 "Homeland Security and Government Affairs" 13 "Indian Affairs" 14 "Intelligence" 15 "Judiciary" 16 "Labor and Human Resources" 17 "Rules and Administration" 18 "Small Business" 19 "Small Business and Entrepreneurship" 20 "Veterans' Affairs") label(labsize(small))) nooutside ///
> ylabel(-200(100)500, nogrid labsize(small)) ///
> note("") ///
> ytitle("Duration of Committee Deliberation", size(small) margin(t=2)) ///
> title("FIGURE 2: Box-Whisker Plots of the Difference in Committee" "Confirmation Delay by Senate Committee for Divided and Unified Government", size(small)) yline(0, lcolor(red%40) lpattern(dash)) xsize(6)
{res}{txt}
{com}. 
. 
. graph save "Graph" "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure2.gph", replace
{res}{txt}file {bf:/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure2.gph} saved

{com}. 
. 
. 
. 
. 
. 
. ************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. use "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Data/Krause and Byers Data (12.17.2024).dta", replace
{txt}
{com}. 
. 
. ********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. ** Generate Descriptive Statistics on Committee Confirmation Delay Based on Regression Sample (Both Uncensored and Full Effective Samples)** 
. 
. sum legvet2 if e(sample) & confirmbinary==1, detail 

                           {txt}legvet2
{hline 61}
no observations

{com}. *
. *
. sum legvet2 if e(sample), detail 

                           {txt}legvet2
{hline 61}
no observations

{com}. 
. 
. 
. 
. 
. 
. 
. **** CREATE NEW AGENCY IDENTIFIER FROM STRING VARIABLE ****
. 
. 
. encode agency, generate(agency_id)
{txt}
{com}. 
. 
. 
. **** CREATE MAJOR POLICY AGENCY BINARY INDICATOR [= 1 FOR MAJOR POLICY-RELATED AGENCIES; = 0 OTHERWISE -- E.G., MINOR COMMISSIONS, COUNCILS, ADVISORY GROUPS, ETC......]
. 
.  
. generate policy_majagency = 1 if agency_id>=1 & agency_id<=2 | agency_id==5 | agency_id==12 | agency_id>=32 & agency_id<=34 | agency_id>=36 & agency_id<=39 | agency_id==41 | agency_id>=43 & agency_id<=45 | agency_id>=50 & agency_id<=51 | agency_id==54 | agency_id >=57 & agency_id<=59 | agency_id==62 | agency_id>=64 & agency_id<=83 | agency_id>=85 & agency_id<=87 | agency_id>=90 & agency_id<=94 | agency_id==96 | agency_id>=98 & agency_id<=104 | agency_id>=106 & agency_id<=107 | agency_id>=110 & agency_id<=112 |  agency_id>=114 & agency_id<=127 | agency_id>=130 & agency_id<=131 | agency_id==136 | agency_id>=146 & agency_id<=148 | agency_id>=150 & agency_id<=152 | agency_id==155 | agency_id>=167 & agency_id<=168 | agency_id==186 | agency_id>=194 & agency_id<=195 | agency_id>=199 & agency_id<=203 | agency_id==205 | agency_id>=208 & agency_id<=222 | agency_id>=226 & agency_id<=227 |agency_id==232 | agency_id>=234 & agency_id<=235 | agency_id>=245 & agency_id<=246 | agency_id>=253 | agency_id==255 | agency_id==260 | agency_id==269 | agency_id==271 | agency_id==274|  agency_id>=277 & agency_id<=279
{txt}(2,718 missing values generated)

{com}. *
. replace policy_majagency = 0 if policy_majagency==.
{txt}(2,718 real changes made)

{com}. *
. *
. tab policy_majagency

{txt}policy_maja {c |}
      gency {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      2,718       26.25       26.25
{txt}          1 {c |}{res}      7,636       73.75      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     10,354      100.00
{txt}
{com}. 
. 
. 
. 
. *** CREATE OUTCOME DURATION VARIABLE AND SET SURVIVAL TIME FUNCTION [STSET] *** 
. 
. 
. generate legvetdur2plus1 = legvet2+1
{txt}(244 missing values generated)

{com}. *
. stset legvetdur2plus1, failure(confirmbinary)

{txt}Survival-time data settings

{col 10}Failure event: {res}confirmbinary!=0 & confirmbinary<.
{col 1}{txt}Observed time interval: {res}(0, legvetdur2plus1]
{col 6}{txt}Exit on or before: {res}failure

{txt}{hline 74}
{res}     10,354{txt}  total observations
{res}        244{txt}  event time missing (legvetdur2plus1>=.){col 61}PROBABLE ERROR
{hline 74}
{res}     10,110{txt}  observations remaining, representing
{res}      7,166{txt}  failures in single-record/single-failure data
{res}    988,097{txt}  total analysis time at risk and under observation
                                                At risk from t = {res}        0
                                     {txt}Earliest observed entry t = {res}        0
                                          {txt}Last observed exit t = {res}      730
{txt}
{com}. 
. *
. *
. *
. 
. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. *****************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. *** COMPUTE DESCRIPTIVE STATISTICS FOR MAIN COVARIATES  ***
. 
. quietly stcox    committee_pres1  chair_pres1     sendivide   pressenfloorabsdist   experience_median  chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck  workload  polarization kv_workload   female priorconfirm  denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social    fvra firstrecess secondrecess policy_majagency  i.kbcom_1 i.presrev, vce(cluster kbcom_1)
{txt}
{com}. 
. 
. 
. 
. 
. *** COMPUTE WITHIN-COMMITTEE DESCRIPTIVE STATISTICS SINCE MODEL ESTIMATES ARE WITHIN-COMMITTEE EFFECTS [SENATE COMMITTEE MEDIAN or SENATE COMMITTEE CHAIR - PRESIDENT ABSOLUTE IDEOLOGICAL DIFFERENCE] *** 
. 
. * FIRST, 'quietly' obtain correct regression model sample *
. 
. quietly stcox    committee_pres1  chair_pres1     sendivide   pressenfloorabsdist   experience_median chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck  workload  polarization kv_workload   female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social  fvra firstrecess secondrecess policy_majagency i.kbcom_1 i.presrev, vce(cluster kbcom_1)
{txt}
{com}. 
. 
. 
. * SECOND, compute within-committee descriptive statistics  for primary continuous covariates *
. 
. * calculate the committee/group-means *
. egen bSenComm_committee_pres1 = mean(committee_pres1), by(kbcom_1)
{txt}(421 missing values generated)

{com}. egen bSenComm_chair_pres1 = mean(chair_pres1), by(kbcom_1)
{txt}(421 missing values generated)

{com}. *
. *
. 
. * compute the within-committee deviations from the respective committee means *
. gen wSenComm_committee_pres1 = committee_pres1 - bSenComm_committee_pres1
{txt}(421 missing values generated)

{com}. gen wSenComm_chair_pres1 =     chair_pres1     - bSenComm_chair_pres1
{txt}(421 missing values generated)

{com}. *
. *
. *
. 
. * compute descriptive statistics for overall measure and within-committee measure *
.  
. sum committee_pres1  wSenComm_committee_pres1 if e(sample), detail

                       {txt}committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}     .032           .032
{txt} 5%    {res}     .049           .032
{txt}10%    {res}      .11           .032       {txt}Obs         {res}      9,879
{txt}25%    {res}     .215           .032       {txt}Sum of wgt. {res}      9,879

{txt}50%    {res}     .529                      {txt}Mean          {res} .4991435
                        {txt}Largest       Std. dev.     {res} .2925072
{txt}75%    {res}     .723           1.02
{txt}90%    {res}     .885           1.02       {txt}Variance      {res} .0855604
{txt}95%    {res}     .959           1.02       {txt}Skewness      {res}-.0129892
{txt}99%    {res}     1.02           1.02       {txt}Kurtosis      {res} 1.780538

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.5386078      -.5386078
{txt} 5%    {res} -.412061      -.5386078
{txt}10%    {res}-.4026805      -.5386078       {txt}Obs         {res}      9,879
{txt}25%    {res}-.2758437      -.5386078       {txt}Sum of wgt. {res}      9,879

{txt}50%    {res} .0419552                      {txt}Mean          {res} .0016981
                        {txt}Largest       Std. dev.     {res} .2860087
{txt}75%    {res} .2273195        .490939
{txt}90%    {res} .3713921        .490939       {txt}Variance      {res} .0818009
{txt}95%    {res} .4655938        .490939       {txt}Skewness      {res} -.081259
{txt}99%    {res}  .490939        .676923       {txt}Kurtosis      {res} 1.813208
{txt}
{com}. *
. sum chair_pres1  wSenComm_chair_pres1 if e(sample), detail

                         {txt}chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}     .002           .001
{txt} 5%    {res}     .006           .001
{txt}10%    {res}     .009           .001       {txt}Obs         {res}      9,879
{txt}25%    {res}     .106           .001       {txt}Sum of wgt. {res}      9,879

{txt}50%    {res}     .452                      {txt}Mean          {res} .5191116
                        {txt}Largest       Std. dev.     {res} .4132145
{txt}75%    {res}     .917           1.29
{txt}90%    {res}    1.053           1.29       {txt}Variance      {res} .1707462
{txt}95%    {res}    1.135           1.29       {txt}Skewness      {res} .1111314
{txt}99%    {res}    1.136           1.29       {txt}Kurtosis      {res} 1.410512

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.7163319      -.7163319
{txt} 5%    {res}-.5251514      -.7163319
{txt}10%    {res}-.4717167      -.7163319       {txt}Obs         {res}      9,879
{txt}25%    {res}-.3927915      -.7163319       {txt}Sum of wgt. {res}      9,879

{txt}50%    {res}-.0447927                      {txt}Mean          {res} .0024217
                        {txt}Largest       Std. dev.     {res} .4044573
{txt}75%    {res} .3837861       .7534087
{txt}90%    {res} .5187862       .7534087       {txt}Variance      {res} .1635857
{txt}95%    {res} .6122074       .7534087       {txt}Skewness      {res} .1112808
{txt}99%    {res} .6940686       .8284615       {txt}Kurtosis      {res} 1.587205
{txt}
{com}. *
. *
. 
. 
. 
. *save "C:\Users\gk57526\Dropbox\Confirmation Dynamics Project (Jason Byers)\Confirmation Delay & Senate Committees\2023 Version\Fall 2024\Statistics\Data\Committee Delay.MANUSCRIPT RESULTS.12-23-2024.dta", replace
. 
. save "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Data/Committee Delay.MANUSCRIPT RESULTS.12-23-2024.dta", replace
{txt}{p 0 4 2}
file {bf}
/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Data/Committee Delay.MANUSCRIPT RESULTS.12-23-2024.dta{rm}
saved
{p_end}

{com}. 
. 
. ***************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
.  
. 
. 
. 
. 
. ** SET UP DATA TO BE READ IN DURATION/SURVIVAL TIME FORM & CREATE REQUISITE INTERACTION VARIABLES TO BE USED IN EVALUATING SELECTIVE VETTING HYPOTHESIS **
. 
. stset legvetdur2plus1, failure(confirmbinary)

{txt}Survival-time data settings

{col 10}Failure event: {res}confirmbinary!=0 & confirmbinary<.
{col 1}{txt}Observed time interval: {res}(0, legvetdur2plus1]
{col 6}{txt}Exit on or before: {res}failure

{txt}{hline 74}
{res}     10,354{txt}  total observations
{res}        244{txt}  event time missing (legvetdur2plus1>=.){col 61}PROBABLE ERROR
{hline 74}
{res}     10,110{txt}  observations remaining, representing
{res}      7,166{txt}  failures in single-record/single-failure data
{res}    988,097{txt}  total analysis time at risk and under observation
                                                At risk from t = {res}        0
                                     {txt}Earliest observed entry t = {res}        0
                                          {txt}Last observed exit t = {res}      730
{txt}
{com}. 
. *
. *
. *
. *
. 
. 
. *** EVALUATING THE PARTISAN SELECTIVE VETTING HYPOTHESIS FOR EXECUTIVE NOMINATIONS [N = 9,879] ***
. 
. 
. 
. 
.  
.  
.  
. ***  FIRST SET OF ANALYSES: COX SEMIPARAMETRIC MODEL ***
. 
. 
. 
. 
. 
. * SENATE COMMITTEE MEDIAN PREFERENCE DISTANCE & UNIFIED/DIVIDED PARTISAN CONTROL OF SENATE & PRESIDENCY [MODEL 1: COX SEMIPARAMETRIC MODEL] *
. 
. stcox   c.committee_pres1##i.sendivide   pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck    kv_workload  polarization  workload      female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency  i.kbcom_1  i.presrev,  vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}Iteration 0:  Log pseudolikelihood = {res}-59700.769
{txt}Iteration 1:  Log pseudolikelihood = {res}-59444.852
{txt}Iteration 2:  Log pseudolikelihood = {res}-58823.808
{txt}Iteration 3:  Log pseudolikelihood = {res}-58769.638
{txt}Iteration 4:  Log pseudolikelihood = {res}-58768.337
{txt}Iteration 5:  Log pseudolikelihood = {res}-58768.336
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-58768.336

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:9,879}{col 54}{txt}{lalign 13:Number of obs} = {res}{ralign 9:9,879}
{txt}No. of failures = {res}{ralign 7:7,076}
{txt}Time at risk    = {res}{ralign 7:987,811}
{col 54}{txt}{lalign 13:Wald chi2({res:19})} = {res}{ralign 9:119508.24}
{txt}Log pseudolikelihood = {res}-58768.336{col 54}{txt}{lalign 13:Prob > chi2} = {res}{ralign 9:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .3455547{col 29}{space 2} .1883303{col 40}{space 1}   -1.95{col 49}{space 3}0.051{col 57}{space 4} .1187421{col 70}{space 3} 1.005609
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .2773871{col 29}{space 2} .1342547{col 40}{space 1}   -2.65{col 49}{space 3}0.008{col 57}{space 4} .1074253{col 70}{space 3} .7162518
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 13}c. {c |}
committee_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 5.537212{col 29}{space 2} 3.225781{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} 1.767713{col 70}{space 3} 17.34485
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} 1.174547{col 29}{space 2}  .801617{col 40}{space 1}    0.24{col 49}{space 3}0.814{col 57}{space 4} .3082717{col 70}{space 3} 4.475146
{txt}experience_me~n {c |}{col 17}{res}{space 2} .9937275{col 29}{space 2} .0109656{col 40}{space 1}   -0.57{col 49}{space 3}0.569{col 57}{space 4} .9724661{col 70}{space 3} 1.015454
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9913674{col 29}{space 2} .0042364{col 40}{space 1}   -2.03{col 49}{space 3}0.042{col 57}{space 4} .9830989{col 70}{space 3} .9997056
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8996046{col 29}{space 2} .0824874{col 40}{space 1}   -1.15{col 49}{space 3}0.249{col 57}{space 4} .7516271{col 70}{space 3} 1.076715
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.002869{col 29}{space 2} .0021664{col 40}{space 1}    1.33{col 49}{space 3}0.185{col 57}{space 4} .9986322{col 70}{space 3} 1.007124
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.778825{col 29}{space 2} .2531011{col 40}{space 1}   11.22{col 49}{space 3}0.000{col 57}{space 4} 2.324513{col 70}{space 3} 3.321929
{txt}{space 3}preselection {c |}{col 17}{res}{space 2}   .68984{col 29}{space 2} .0427717{col 40}{space 1}   -5.99{col 49}{space 3}0.000{col 57}{space 4} .6109026{col 70}{space 3} .7789773
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8712973{col 29}{space 2} .0632321{col 40}{space 1}   -1.90{col 49}{space 3}0.058{col 57}{space 4} .7557752{col 70}{space 3} 1.004477
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999838{col 29}{space 2} .0000325{col 40}{space 1}   -0.50{col 49}{space 3}0.618{col 57}{space 4}   .99992{col 70}{space 3} 1.000048
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0624136{col 29}{space 2} .0779486{col 40}{space 1}   -2.22{col 49}{space 3}0.026{col 57}{space 4} .0053977{col 70}{space 3} .7216852
{txt}{space 7}workload {c |}{col 17}{res}{space 2}   1.0021{col 29}{space 2} .0013188{col 40}{space 1}    1.59{col 49}{space 3}0.111{col 57}{space 4} .9995182{col 70}{space 3} 1.004688
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.002407{col 29}{space 2} .0422175{col 40}{space 1}    0.06{col 49}{space 3}0.954{col 57}{space 4} .9229852{col 70}{space 3} 1.088663
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2} .9798169{col 29}{space 2} .0475901{col 40}{space 1}   -0.42{col 49}{space 3}0.675{col 57}{space 4} .8908441{col 70}{space 3} 1.077676
{txt}{space 9}denied {c |}{col 17}{res}{space 2} .6713738{col 29}{space 2} .0668592{col 40}{space 1}   -4.00{col 49}{space 3}0.000{col 57}{space 4} .5523278{col 70}{space 3} .8160785
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9549586{col 29}{space 2} .0434339{col 40}{space 1}   -1.01{col 49}{space 3}0.311{col 57}{space 4} .8735137{col 70}{space 3} 1.043997
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2}  .829986{col 29}{space 2} .1437083{col 40}{space 1}   -1.08{col 49}{space 3}0.282{col 57}{space 4} .5911383{col 70}{space 3} 1.165339
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .8171359{col 29}{space 2}  .094521{col 40}{space 1}   -1.75{col 49}{space 3}0.081{col 57}{space 4} .6513776{col 70}{space 3} 1.025075
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9771073{col 29}{space 2} .0847063{col 40}{space 1}   -0.27{col 49}{space 3}0.789{col 57}{space 4} .8244245{col 70}{space 3} 1.158067
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9539615{col 29}{space 2} .0672643{col 40}{space 1}   -0.67{col 49}{space 3}0.504{col 57}{space 4}   .83083{col 70}{space 3} 1.095342
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9088689{col 29}{space 2} .0601476{col 40}{space 1}   -1.44{col 49}{space 3}0.149{col 57}{space 4} .7983071{col 70}{space 3} 1.034743
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.205004{col 29}{space 2} .0780931{col 40}{space 1}    2.88{col 49}{space 3}0.004{col 57}{space 4} 1.061267{col 70}{space 3}  1.36821
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9604631{col 29}{space 2} .0423939{col 40}{space 1}   -0.91{col 49}{space 3}0.361{col 57}{space 4} .8808653{col 70}{space 3} 1.047254
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2}  .752986{col 29}{space 2}  .064556{col 40}{space 1}   -3.31{col 49}{space 3}0.001{col 57}{space 4} .6365177{col 70}{space 3} .8907652
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.252151{col 29}{space 2} .0792763{col 40}{space 1}    3.55{col 49}{space 3}0.000{col 57}{space 4} 1.106026{col 70}{space 3} 1.417581
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.048023{col 29}{space 2}  .131445{col 40}{space 1}    0.37{col 49}{space 3}0.708{col 57}{space 4} .8196179{col 70}{space 3} 1.340078
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .9298937{col 29}{space 2} .0699643{col 40}{space 1}   -0.97{col 49}{space 3}0.334{col 57}{space 4} .8023978{col 70}{space 3} 1.077648
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 3.324175{col 29}{space 2} .4093977{col 40}{space 1}    9.75{col 49}{space 3}0.000{col 57}{space 4}  2.61127{col 70}{space 3}  4.23171
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.296319{col 29}{space 2} .2102755{col 40}{space 1}    1.60{col 49}{space 3}0.110{col 57}{space 4} .9432761{col 70}{space 3} 1.781497
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.522082{col 29}{space 2} .2131595{col 40}{space 1}    3.00{col 49}{space 3}0.003{col 57}{space 4}  1.15673{col 70}{space 3} 2.002831
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.082441{col 29}{space 2} .1032359{col 40}{space 1}    0.83{col 49}{space 3}0.406{col 57}{space 4} .8978882{col 70}{space 3} 1.304926
{txt}{space 13}8  {c |}{col 17}{res}{space 2} .9988801{col 29}{space 2} .2681799{col 40}{space 1}   -0.00{col 49}{space 3}0.997{col 57}{space 4} .5901771{col 70}{space 3} 1.690614
{txt}{space 13}9  {c |}{col 17}{res}{space 2} .9645213{col 29}{space 2} .1199263{col 40}{space 1}   -0.29{col 49}{space 3}0.771{col 57}{space 4} .7559193{col 70}{space 3} 1.230689
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .8017091{col 29}{space 2} .1922305{col 40}{space 1}   -0.92{col 49}{space 3}0.357{col 57}{space 4} .5010941{col 70}{space 3} 1.282668
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.207639{col 29}{space 2}  .310747{col 40}{space 1}    0.73{col 49}{space 3}0.463{col 57}{space 4} .7293025{col 70}{space 3} 1.999707
{txt}{space 12}12  {c |}{col 17}{res}{space 2}  1.21705{col 29}{space 2} .4085773{col 40}{space 1}    0.59{col 49}{space 3}0.558{col 57}{space 4} .6303043{col 70}{space 3} 2.349991
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .6589624{col 29}{space 2} .0624533{col 40}{space 1}   -4.40{col 49}{space 3}0.000{col 57}{space 4} .5472526{col 70}{space 3} .7934753
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.190897{col 29}{space 2} .2726561{col 40}{space 1}    0.76{col 49}{space 3}0.445{col 57}{space 4} .7603112{col 70}{space 3} 1.865335
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 1.780831{col 29}{space 2} .6736178{col 40}{space 1}    1.53{col 49}{space 3}0.127{col 57}{space 4} .8484903{col 70}{space 3} 3.737649
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.235201{col 29}{space 2} .3622805{col 40}{space 1}    0.72{col 49}{space 3}0.471{col 57}{space 4} .6951573{col 70}{space 3} 2.194787
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5996267{col 29}{space 2} .0814234{col 40}{space 1}   -3.77{col 49}{space 3}0.000{col 57}{space 4} .4595113{col 70}{space 3} .7824665
{txt}{space 12}18  {c |}{col 17}{res}{space 2}  .770591{col 29}{space 2} .2015812{col 40}{space 1}   -1.00{col 49}{space 3}0.319{col 57}{space 4} .4614829{col 70}{space 3} 1.286744
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .4996158{col 29}{space 2} .0510183{col 40}{space 1}   -6.80{col 49}{space 3}0.000{col 57}{space 4} .4089927{col 70}{space 3} .6103187
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .8718078{col 29}{space 2} .0750779{col 40}{space 1}   -1.59{col 49}{space 3}0.111{col 57}{space 4} .7364062{col 70}{space 3} 1.032106
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.664653{col 29}{space 2} .3593316{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} 1.090395{col 70}{space 3} 2.541347
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.603092{col 29}{space 2} .4620934{col 40}{space 1}    1.64{col 49}{space 3}0.102{col 57}{space 4} .9111681{col 70}{space 3}  2.82045
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.446869{col 29}{space 2} .3541315{col 40}{space 1}    1.51{col 49}{space 3}0.131{col 57}{space 4} .8955534{col 70}{space 3} 2.337582
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.043466{col 29}{space 2}  .346877{col 40}{space 1}    0.13{col 49}{space 3}0.898{col 57}{space 4} .5438955{col 70}{space 3} 2.001895
{txt}{space 13}6  {c |}{col 17}{res}{space 2} .8768419{col 29}{space 2} .3799191{col 40}{space 1}   -0.30{col 49}{space 3}0.762{col 57}{space 4} .3750695{col 70}{space 3} 2.049891
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}     9,879{col 28}-59700.77{col 39}-58768.34{col 50}    19{col 58} 117574.7{col 69} 117711.4
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. estimates store model1
{txt}
{com}. estout model1, cells(b(star fmt(3)) se(par fmt(3))) eform
{res}
{txt}{hline 28}
{txt}                   model1   
{txt}                     b/se   
{txt}{hline 28}
{txt}committee_~1{res}        0.346   {txt}
            {res}      (0.188)   {txt}
{txt}0.sendivide {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivide {res}        0.277** {txt}
            {res}      (0.134)   {txt}
{txt}0.sendivid~1{res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivid~1{res}        5.537** {txt}
            {res}      (3.226)   {txt}
{txt}pressenflo~t{res}        1.175   {txt}
            {res}      (0.802)   {txt}
{txt}experience~n{res}        0.994   {txt}
            {res}      (0.011)   {txt}
{txt}committees~e{res}        0.991*  {txt}
            {res}      (0.004)   {txt}
{txt}ln_combill~d{res}        0.900   {txt}
            {res}      (0.082)   {txt}
{txt}pres_app_m  {res}        1.003   {txt}
            {res}      (0.002)   {txt}
{txt}first90     {res}        2.779***{txt}
            {res}      (0.253)   {txt}
{txt}preselection{res}        0.690***{txt}
            {res}      (0.043)   {txt}
{txt}lameduck    {res}        0.871   {txt}
            {res}      (0.063)   {txt}
{txt}kv_workload {res}        1.000   {txt}
            {res}      (0.000)   {txt}
{txt}polarization{res}        0.062*  {txt}
            {res}      (0.078)   {txt}
{txt}workload    {res}        1.002   {txt}
            {res}      (0.001)   {txt}
{txt}female      {res}        1.002   {txt}
            {res}      (0.042)   {txt}
{txt}priorconfirm{res}        0.980   {txt}
            {res}      (0.048)   {txt}
{txt}denied      {res}        0.671***{txt}
            {res}      (0.067)   {txt}
{txt}x_itier_2   {res}        0.955   {txt}
            {res}      (0.043)   {txt}
{txt}x_itier_3   {res}        0.830   {txt}
            {res}      (0.144)   {txt}
{txt}x_itier_4   {res}        0.817   {txt}
            {res}      (0.095)   {txt}
{txt}defense     {res}        0.977   {txt}
            {res}      (0.085)   {txt}
{txt}infrastruc~e{res}        0.954   {txt}
            {res}      (0.067)   {txt}
{txt}social      {res}        0.909   {txt}
            {res}      (0.060)   {txt}
{txt}fvra        {res}        1.205** {txt}
            {res}      (0.078)   {txt}
{txt}firstrecess {res}        0.960   {txt}
            {res}      (0.042)   {txt}
{txt}secondrecess{res}        0.753***{txt}
            {res}      (0.065)   {txt}
{txt}policy_maj~y{res}        1.252***{txt}
            {res}      (0.079)   {txt}
{txt}1.kbcom_1   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.kbcom_1   {res}        1.048   {txt}
            {res}      (0.131)   {txt}
{txt}3.kbcom_1   {res}        0.930   {txt}
            {res}      (0.070)   {txt}
{txt}4.kbcom_1   {res}        3.324***{txt}
            {res}      (0.409)   {txt}
{txt}5.kbcom_1   {res}        1.296   {txt}
            {res}      (0.210)   {txt}
{txt}6.kbcom_1   {res}        1.522** {txt}
            {res}      (0.213)   {txt}
{txt}7.kbcom_1   {res}        1.082   {txt}
            {res}      (0.103)   {txt}
{txt}8.kbcom_1   {res}        0.999   {txt}
            {res}      (0.268)   {txt}
{txt}9.kbcom_1   {res}        0.965   {txt}
            {res}      (0.120)   {txt}
{txt}10.kbcom_1  {res}        0.802   {txt}
            {res}      (0.192)   {txt}
{txt}11.kbcom_1  {res}        1.208   {txt}
            {res}      (0.311)   {txt}
{txt}12.kbcom_1  {res}        1.217   {txt}
            {res}      (0.409)   {txt}
{txt}13.kbcom_1  {res}        0.659***{txt}
            {res}      (0.062)   {txt}
{txt}14.kbcom_1  {res}        1.191   {txt}
            {res}      (0.273)   {txt}
{txt}15.kbcom_1  {res}        1.781   {txt}
            {res}      (0.674)   {txt}
{txt}16.kbcom_1  {res}        1.235   {txt}
            {res}      (0.362)   {txt}
{txt}17.kbcom_1  {res}        0.600***{txt}
            {res}      (0.081)   {txt}
{txt}18.kbcom_1  {res}        0.771   {txt}
            {res}      (0.202)   {txt}
{txt}19.kbcom_1  {res}        0.500***{txt}
            {res}      (0.051)   {txt}
{txt}20.kbcom_1  {res}        0.872   {txt}
            {res}      (0.075)   {txt}
{txt}1.presrev   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.presrev   {res}        1.665*  {txt}
            {res}      (0.359)   {txt}
{txt}3.presrev   {res}        1.603   {txt}
            {res}      (0.462)   {txt}
{txt}4.presrev   {res}        1.447   {txt}
            {res}      (0.354)   {txt}
{txt}5.presrev   {res}        1.043   {txt}
            {res}      (0.347)   {txt}
{txt}6.presrev   {res}        0.877   {txt}
            {res}      (0.380)   {txt}
{txt}{hline 28}

{com}. 
. 
. *
. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME *
. sum wSenComm_committee_pres1 if e(sample) & sendivide==0, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.5386078      -.5386078
{txt} 5%    {res}-.4312148      -.5386078
{txt}10%    {res} -.412061      -.5386078       {txt}Obs         {res}      5,188
{txt}25%    {res}-.3654062      -.5386078       {txt}Sum of wgt. {res}      5,188

{txt}50%    {res}-.2720448                      {txt}Mean          {res}-.1849183
                        {txt}Largest       Std. dev.     {res} .2315506
{txt}75%    {res}-.0624062        .490939
{txt}90%    {res} .1603195        .490939       {txt}Variance      {res} .0536157
{txt}95%    {res} .2121217        .490939       {txt}Skewness      {res} .7437833
{txt}99%    {res} .4655938        .490939       {txt}Kurtosis      {res} 2.725898
{txt}
{com}. sum wSenComm_committee_pres1 if e(sample) & sendivide==1, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.1966079      -.5386078
{txt} 5%    {res}-.1966079      -.2916805
{txt}10%    {res}-.0414062      -.2201461       {txt}Obs         {res}      4,691
{txt}25%    {res} .0904305      -.1966079       {txt}Sum of wgt. {res}      4,691

{txt}50%    {res} .2273195                      {txt}Mean          {res}  .208086
                        {txt}Largest       Std. dev.     {res} .1784988
{txt}75%    {res} .3387852        .490939
{txt}90%    {res} .4655938        .490939       {txt}Variance      {res} .0318618
{txt}95%    {res} .4706168        .490939       {txt}Skewness      {res}-.4131515
{txt}99%    {res}  .490939        .676923       {txt}Kurtosis      {res} 2.718282
{txt}
{com}. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"  *
. lincomest (committee_pres1 * 0.303 +  1.sendivide#c.committee_pres1 * 0.2483547) - committee_pres1 * 0.303, eform(hr)
{txt}Confidence interval for formula:
{res}(committee_pres1*0.303+1.sendivide#c.committee_pres1*0.2483547)-committee_pres1*0.303

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.529677{col 26}{space 2} .2213176{col 37}{space 1}    2.94{col 46}{space 3}0.003{col 54}{space 4} 1.151982{col 67}{space 3} 2.031205
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model1 = r(table)
{txt}
{com}. mat list model1
{res}
{txt}model1[9,1]
               (1)
     b {res} 1.5296774
{txt}    se {res} .22131758
{txt}     z {res}  2.937859
{txt}pvalue {res} .00330487
{txt}    ll {res} 1.1519824
{txt}    ul {res} 2.0312054
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. *
. *
. *
. 
. 
. 
. 
. ** STORE FINAL SET OF RESULTS FOR FIGURE 2 BELOW ****
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. 
.   
. 
. 
. * SENATE COMMITTEE CHAIR PREFERENCE DISTANCE & UNIFIED/DIVIDED PARTISAN CONTROL OF SENATE & PRESIDENCY [MODEL 2: COX SEMIPARAMETRIC MODEL] *
. 
. 
. stcox   c.chair_pres1##i.sendivide   pressenfloorabsdist  chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck    kv_workload  polarization  workload      female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency  i.kbcom_1  i.presrev,  vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}Iteration 0:  Log pseudolikelihood = {res}-59700.769
{txt}Iteration 1:  Log pseudolikelihood = {res}-59444.319
{txt}Iteration 2:  Log pseudolikelihood = {res}-58828.445
{txt}Iteration 3:  Log pseudolikelihood = {res} -58775.24
{txt}Iteration 4:  Log pseudolikelihood = {res}-58773.983
{txt}Iteration 5:  Log pseudolikelihood = {res}-58773.981
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-58773.981

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:9,879}{col 56}{txt}{lalign 13:Number of obs} = {res}{ralign 7:9,879}
{txt}No. of failures = {res}{ralign 7:7,076}
{txt}Time at risk    = {res}{ralign 7:987,811}
{col 56}{txt}{lalign 13:Wald chi2({res:19})} = {res}{ralign 7:4482.08}
{txt}Log pseudolikelihood = {res}-58773.981{col 56}{txt}{lalign 13:Prob > chi2} = {res}{ralign 7:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .7760439{col 29}{space 2} .1929007{col 40}{space 1}   -1.02{col 49}{space 3}0.308{col 57}{space 4} .4767643{col 70}{space 3} 1.263191
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .4044983{col 29}{space 2} .1307124{col 40}{space 1}   -2.80{col 49}{space 3}0.005{col 57}{space 4} .2147106{col 70}{space 3} .7620439
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 2}c.chair_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 2.538605{col 29}{space 2} .8830996{col 40}{space 1}    2.68{col 49}{space 3}0.007{col 57}{space 4} 1.283776{col 70}{space 3} 5.019968
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} .6742548{col 29}{space 2} .4159716{col 40}{space 1}   -0.64{col 49}{space 3}0.523{col 57}{space 4} .2012277{col 70}{space 3} 2.259229
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.004468{col 29}{space 2} .0028506{col 40}{space 1}    1.57{col 49}{space 3}0.116{col 57}{space 4} .9988966{col 70}{space 3} 1.010071
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9917161{col 29}{space 2} .0045577{col 40}{space 1}   -1.81{col 49}{space 3}0.070{col 57}{space 4} .9828232{col 70}{space 3} 1.000689
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8708798{col 29}{space 2} .0746124{col 40}{space 1}   -1.61{col 49}{space 3}0.107{col 57}{space 4} .7362608{col 70}{space 3} 1.030113
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.002874{col 29}{space 2} .0019474{col 40}{space 1}    1.48{col 49}{space 3}0.139{col 57}{space 4} .9990647{col 70}{space 3} 1.006698
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.840088{col 29}{space 2} .2372863{col 40}{space 1}   12.49{col 49}{space 3}0.000{col 57}{space 4} 2.411097{col 70}{space 3} 3.345405
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .6791698{col 29}{space 2} .0441771{col 40}{space 1}   -5.95{col 49}{space 3}0.000{col 57}{space 4} .5978763{col 70}{space 3} .7715169
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8580077{col 29}{space 2} .0674126{col 40}{space 1}   -1.95{col 49}{space 3}0.051{col 57}{space 4}  .735552{col 70}{space 3}  1.00085
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999934{col 29}{space 2} .0000344{col 40}{space 1}   -0.19{col 49}{space 3}0.848{col 57}{space 4}  .999926{col 70}{space 3} 1.000061
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0390824{col 29}{space 2} .0499407{col 40}{space 1}   -2.54{col 49}{space 3}0.011{col 57}{space 4} .0031937{col 70}{space 3} .4782705
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.001944{col 29}{space 2} .0013057{col 40}{space 1}    1.49{col 49}{space 3}0.136{col 57}{space 4} .9993884{col 70}{space 3} 1.004507
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.000002{col 29}{space 2} .0425108{col 40}{space 1}    0.00{col 49}{space 3}1.000{col 57}{space 4} .9200586{col 70}{space 3} 1.086891
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2} .9714085{col 29}{space 2} .0486952{col 40}{space 1}   -0.58{col 49}{space 3}0.563{col 57}{space 4} .8805063{col 70}{space 3} 1.071695
{txt}{space 9}denied {c |}{col 17}{res}{space 2} .6699858{col 29}{space 2} .0687291{col 40}{space 1}   -3.90{col 49}{space 3}0.000{col 57}{space 4} .5479576{col 70}{space 3} .8191893
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9380745{col 29}{space 2} .0450069{col 40}{space 1}   -1.33{col 49}{space 3}0.183{col 57}{space 4} .8538831{col 70}{space 3} 1.030567
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .8188279{col 29}{space 2}  .139745{col 40}{space 1}   -1.17{col 49}{space 3}0.242{col 57}{space 4} .5860337{col 70}{space 3} 1.144097
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .8138179{col 29}{space 2} .0953996{col 40}{space 1}   -1.76{col 49}{space 3}0.079{col 57}{space 4} .6467633{col 70}{space 3} 1.024021
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9911122{col 29}{space 2} .0797583{col 40}{space 1}   -0.11{col 49}{space 3}0.912{col 57}{space 4} .8464935{col 70}{space 3} 1.160438
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9476811{col 29}{space 2} .0627155{col 40}{space 1}   -0.81{col 49}{space 3}0.417{col 57}{space 4}  .832399{col 70}{space 3} 1.078929
{txt}{space 9}social {c |}{col 17}{res}{space 2}  .922414{col 29}{space 2} .0646143{col 40}{space 1}   -1.15{col 49}{space 3}0.249{col 57}{space 4} .8040813{col 70}{space 3} 1.058161
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.212911{col 29}{space 2}  .079972{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} 1.065874{col 70}{space 3} 1.380232
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9591079{col 29}{space 2} .0422302{col 40}{space 1}   -0.95{col 49}{space 3}0.343{col 57}{space 4} .8798091{col 70}{space 3} 1.045554
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .7629139{col 29}{space 2} .0626558{col 40}{space 1}   -3.30{col 49}{space 3}0.001{col 57}{space 4} .6494848{col 70}{space 3} .8961529
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.267639{col 29}{space 2} .0834161{col 40}{space 1}    3.60{col 49}{space 3}0.000{col 57}{space 4} 1.114251{col 70}{space 3} 1.442143
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .9782769{col 29}{space 2} .0882643{col 40}{space 1}   -0.24{col 49}{space 3}0.808{col 57}{space 4} .8197148{col 70}{space 3} 1.167511
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .9569755{col 29}{space 2} .0585907{col 40}{space 1}   -0.72{col 49}{space 3}0.473{col 57}{space 4} .8487623{col 70}{space 3} 1.078985
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 3.281889{col 29}{space 2} .4241654{col 40}{space 1}    9.20{col 49}{space 3}0.000{col 57}{space 4} 2.547481{col 70}{space 3} 4.228018
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.280477{col 29}{space 2} .1931067{col 40}{space 1}    1.64{col 49}{space 3}0.101{col 57}{space 4}  .952804{col 70}{space 3} 1.720839
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.574111{col 29}{space 2} .1927769{col 40}{space 1}    3.70{col 49}{space 3}0.000{col 57}{space 4} 1.238201{col 70}{space 3}  2.00115
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.139702{col 29}{space 2} .1056958{col 40}{space 1}    1.41{col 49}{space 3}0.159{col 57}{space 4} .9502789{col 70}{space 3} 1.366884
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.051587{col 29}{space 2} .2749913{col 40}{space 1}    0.19{col 49}{space 3}0.847{col 57}{space 4} .6298758{col 70}{space 3}  1.75564
{txt}{space 13}9  {c |}{col 17}{res}{space 2} .9665999{col 29}{space 2} .1091904{col 40}{space 1}   -0.30{col 49}{space 3}0.764{col 57}{space 4} .7746261{col 70}{space 3}  1.20615
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .8307553{col 29}{space 2} .2138129{col 40}{space 1}   -0.72{col 49}{space 3}0.471{col 57}{space 4} .5016466{col 70}{space 3} 1.375778
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.299725{col 29}{space 2} .3481062{col 40}{space 1}    0.98{col 49}{space 3}0.328{col 57}{space 4} .7689064{col 70}{space 3} 2.196996
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.294101{col 29}{space 2}  .464408{col 40}{space 1}    0.72{col 49}{space 3}0.472{col 57}{space 4} .6404742{col 70}{space 3} 2.614779
{txt}{space 12}13  {c |}{col 17}{res}{space 2}  .736885{col 29}{space 2} .0713181{col 40}{space 1}   -3.15{col 49}{space 3}0.002{col 57}{space 4} .6095618{col 70}{space 3} .8908032
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.078282{col 29}{space 2} .2161132{col 40}{space 1}    0.38{col 49}{space 3}0.707{col 57}{space 4} .7279997{col 70}{space 3} 1.597104
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 1.757308{col 29}{space 2} .6832828{col 40}{space 1}    1.45{col 49}{space 3}0.147{col 57}{space 4} .8201262{col 70}{space 3} 3.765435
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.318149{col 29}{space 2} .4000713{col 40}{space 1}    0.91{col 49}{space 3}0.363{col 57}{space 4} .7271372{col 70}{space 3} 2.389531
{txt}{space 12}17  {c |}{col 17}{res}{space 2}  .618598{col 29}{space 2} .0875526{col 40}{space 1}   -3.39{col 49}{space 3}0.001{col 57}{space 4} .4687428{col 70}{space 3} .8163614
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .7344652{col 29}{space 2} .1789508{col 40}{space 1}   -1.27{col 49}{space 3}0.205{col 57}{space 4} .4555939{col 70}{space 3} 1.184035
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5149467{col 29}{space 2} .0474435{col 40}{space 1}   -7.20{col 49}{space 3}0.000{col 57}{space 4} .4298716{col 70}{space 3}  .616859
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .8877642{col 29}{space 2} .0831071{col 40}{space 1}   -1.27{col 49}{space 3}0.203{col 57}{space 4}  .738947{col 70}{space 3} 1.066552
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.600815{col 29}{space 2} .3368994{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4} 1.059745{col 70}{space 3} 2.418135
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.503927{col 29}{space 2} .4549462{col 40}{space 1}    1.35{col 49}{space 3}0.177{col 57}{space 4} .8312538{col 70}{space 3} 2.720946
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.408349{col 29}{space 2} .4144051{col 40}{space 1}    1.16{col 49}{space 3}0.245{col 57}{space 4} .7911249{col 70}{space 3} 2.507121
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.140423{col 29}{space 2} .4193996{col 40}{space 1}    0.36{col 49}{space 3}0.721{col 57}{space 4} .5546637{col 70}{space 3}  2.34478
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.139262{col 29}{space 2} .4428861{col 40}{space 1}    0.34{col 49}{space 3}0.737{col 57}{space 4}  .531766{col 70}{space 3} 2.440769
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}     9,879{col 28}-59700.77{col 39}-58773.98{col 50}    19{col 58}   117586{col 69} 117722.7
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. estimates store model2
{txt}
{com}. estout model2, cells(b(star fmt(3)) se(par fmt(3))) eform
{res}
{txt}{hline 28}
{txt}                   model2   
{txt}                     b/se   
{txt}{hline 28}
{txt}chair_pres1 {res}        0.776   {txt}
            {res}      (0.193)   {txt}
{txt}0.sendivide {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivide {res}        0.404** {txt}
            {res}      (0.131)   {txt}
{txt}0.sendivid~1{res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivid~1{res}        2.539** {txt}
            {res}      (0.883)   {txt}
{txt}pressenflo~t{res}        0.674   {txt}
            {res}      (0.416)   {txt}
{txt}chair_expe~1{res}        1.004   {txt}
            {res}      (0.003)   {txt}
{txt}committees~e{res}        0.992   {txt}
            {res}      (0.005)   {txt}
{txt}ln_combill~d{res}        0.871   {txt}
            {res}      (0.075)   {txt}
{txt}pres_app_m  {res}        1.003   {txt}
            {res}      (0.002)   {txt}
{txt}first90     {res}        2.840***{txt}
            {res}      (0.237)   {txt}
{txt}preselection{res}        0.679***{txt}
            {res}      (0.044)   {txt}
{txt}lameduck    {res}        0.858   {txt}
            {res}      (0.067)   {txt}
{txt}kv_workload {res}        1.000   {txt}
            {res}      (0.000)   {txt}
{txt}polarization{res}        0.039*  {txt}
            {res}      (0.050)   {txt}
{txt}workload    {res}        1.002   {txt}
            {res}      (0.001)   {txt}
{txt}female      {res}        1.000   {txt}
            {res}      (0.043)   {txt}
{txt}priorconfirm{res}        0.971   {txt}
            {res}      (0.049)   {txt}
{txt}denied      {res}        0.670***{txt}
            {res}      (0.069)   {txt}
{txt}x_itier_2   {res}        0.938   {txt}
            {res}      (0.045)   {txt}
{txt}x_itier_3   {res}        0.819   {txt}
            {res}      (0.140)   {txt}
{txt}x_itier_4   {res}        0.814   {txt}
            {res}      (0.095)   {txt}
{txt}defense     {res}        0.991   {txt}
            {res}      (0.080)   {txt}
{txt}infrastruc~e{res}        0.948   {txt}
            {res}      (0.063)   {txt}
{txt}social      {res}        0.922   {txt}
            {res}      (0.065)   {txt}
{txt}fvra        {res}        1.213** {txt}
            {res}      (0.080)   {txt}
{txt}firstrecess {res}        0.959   {txt}
            {res}      (0.042)   {txt}
{txt}secondrecess{res}        0.763***{txt}
            {res}      (0.063)   {txt}
{txt}policy_maj~y{res}        1.268***{txt}
            {res}      (0.083)   {txt}
{txt}1.kbcom_1   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.kbcom_1   {res}        0.978   {txt}
            {res}      (0.088)   {txt}
{txt}3.kbcom_1   {res}        0.957   {txt}
            {res}      (0.059)   {txt}
{txt}4.kbcom_1   {res}        3.282***{txt}
            {res}      (0.424)   {txt}
{txt}5.kbcom_1   {res}        1.280   {txt}
            {res}      (0.193)   {txt}
{txt}6.kbcom_1   {res}        1.574***{txt}
            {res}      (0.193)   {txt}
{txt}7.kbcom_1   {res}        1.140   {txt}
            {res}      (0.106)   {txt}
{txt}8.kbcom_1   {res}        1.052   {txt}
            {res}      (0.275)   {txt}
{txt}9.kbcom_1   {res}        0.967   {txt}
            {res}      (0.109)   {txt}
{txt}10.kbcom_1  {res}        0.831   {txt}
            {res}      (0.214)   {txt}
{txt}11.kbcom_1  {res}        1.300   {txt}
            {res}      (0.348)   {txt}
{txt}12.kbcom_1  {res}        1.294   {txt}
            {res}      (0.464)   {txt}
{txt}13.kbcom_1  {res}        0.737** {txt}
            {res}      (0.071)   {txt}
{txt}14.kbcom_1  {res}        1.078   {txt}
            {res}      (0.216)   {txt}
{txt}15.kbcom_1  {res}        1.757   {txt}
            {res}      (0.683)   {txt}
{txt}16.kbcom_1  {res}        1.318   {txt}
            {res}      (0.400)   {txt}
{txt}17.kbcom_1  {res}        0.619***{txt}
            {res}      (0.088)   {txt}
{txt}18.kbcom_1  {res}        0.734   {txt}
            {res}      (0.179)   {txt}
{txt}19.kbcom_1  {res}        0.515***{txt}
            {res}      (0.047)   {txt}
{txt}20.kbcom_1  {res}        0.888   {txt}
            {res}      (0.083)   {txt}
{txt}1.presrev   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.presrev   {res}        1.601*  {txt}
            {res}      (0.337)   {txt}
{txt}3.presrev   {res}        1.504   {txt}
            {res}      (0.455)   {txt}
{txt}4.presrev   {res}        1.408   {txt}
            {res}      (0.414)   {txt}
{txt}5.presrev   {res}        1.140   {txt}
            {res}      (0.419)   {txt}
{txt}6.presrev   {res}        1.139   {txt}
            {res}      (0.443)   {txt}
{txt}{hline 28}

{com}. *
. *
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME *
. sum wSenComm_chair_pres1 if e(sample) & sendivide==0, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.7163319      -.7163319
{txt} 5%    {res}-.5493055      -.7163319
{txt}10%    {res}-.5251514      -.7163319       {txt}Obs         {res}      5,188
{txt}25%    {res}-.4552139      -.7163319       {txt}Sum of wgt. {res}      5,188

{txt}50%    {res}-.3632139                      {txt}Mean          {res}-.3108356
                        {txt}Largest       Std. dev.     {res} .2508708
{txt}75%    {res}-.1827927       .6940686
{txt}90%    {res}-.0447927       .6940686       {txt}Variance      {res} .0629362
{txt}95%    {res} .1718941       .6940686       {txt}Skewness      {res} 1.832556
{txt}99%    {res} .6122074       .6940686       {txt}Kurtosis      {res} 7.245385
{txt}
{com}. sum wSenComm_chair_pres1 if e(sample) & sendivide==1, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.2693319      -.7163319
{txt} 5%    {res}-.0833319      -.4493055
{txt}10%    {res} .0763208       -.411764       {txt}Obs         {res}      4,691
{txt}25%    {res} .2528486      -.3632139       {txt}Sum of wgt. {res}      4,691

{txt}50%    {res} .3532833                      {txt}Mean          {res} .3488678
                        {txt}Largest       Std. dev.     {res} .2152569
{txt}75%    {res} .4892833       .7534087
{txt}90%    {res} .6122074       .7534087       {txt}Variance      {res} .0463355
{txt}95%    {res} .6940686       .7534087       {txt}Skewness      {res}-.6841008
{txt}99%    {res} .7534087       .8284615       {txt}Kurtosis      {res} 3.657556
{txt}
{com}. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1" *
. lincomest (chair_pres1 * 0.2724212 +  1.sendivide#c.chair_pres1 * 0.2364347) - chair_pres1 * 0.2724212, eform(hr)
{txt}Confidence interval for formula:
{res}(chair_pres1*0.2724212+1.sendivide#c.chair_pres1*0.2364347)-chair_pres1*0.2724212

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.246408{col 26}{space 2} .1025147{col 37}{space 1}    2.68{col 46}{space 3}0.007{col 54}{space 4} 1.060842{col 67}{space 3} 1.464435
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model2 = r(table)
{txt}
{com}. mat list model2
{res}
{txt}model2[9,1]
               (1)
     b {res} 1.2464083
{txt}    se {res} .10251469
{txt}     z {res} 2.6780695
{txt}pvalue {res} .00740478
{txt}    ll {res} 1.0608419
{txt}    ul {res} 1.4644348
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. *
. *
. *
. *
. *
. 
. 
. ** STORE FINAL SET OF RESULTS FOR FIGURE 2 BELOW ****
. 
. 
. 
. 
. 
. 
. 
. 
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. 
. 
.  
.  
.  
. ***  SECOND SET OF ANALYSES: WEIBULL PARAMETRIC MODEL ***
. 
. 
. 
. 
. 
. *** EVALUATING THE PARTISAN SELECTIVE VETTING HYPOTHESIS FOR EXECUTIVE NOMINATIONS [N = 9,879] ***
. 
. 
. 
. 
. * SENATE COMMITTEE MEDIAN PREFERENCE DISTANCE & UNIFIED/DIVIDED PARTISAN CONTROL OF SENATE & PRESIDENCY [MODEL 3: WEIBULL PARAMETRIC MODEL] *
. 
. streg   c.committee_pres1##i.sendivide  pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck    kv_workload  polarization  workload      female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency   i.kbcom_1 i.presrev, distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-14114.273
{txt}Iteration 1:  Log pseudolikelihood = {res}-14091.777
{txt}Iteration 2:  Log pseudolikelihood = {res}-14091.776

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-14091.776}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-13949.799}  
Iteration 2:{space 2}Log pseudolikelihood = {res: -13092.61}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-13067.546}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-13067.462}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-13067.462}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:9,879}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:9,879}
{txt}No. of failures = {res}{ralign 7:7,076}
{txt}Time at risk    = {res}{ralign 7:987,811}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(17)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-13067.462{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .3322358{col 29}{space 2} .2383764{col 40}{space 1}   -1.54{col 49}{space 3}0.125{col 57}{space 4} .0814172{col 70}{space 3}  1.35574
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .2362705{col 29}{space 2} .1349489{col 40}{space 1}   -2.53{col 49}{space 3}0.012{col 57}{space 4} .0771321{col 70}{space 3} .7237425
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 13}c. {c |}
committee_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 7.102962{col 29}{space 2} 4.737623{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} 1.921739{col 70}{space 3} 26.25334
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2}  .914681{col 29}{space 2} .8060492{col 40}{space 1}   -0.10{col 49}{space 3}0.919{col 57}{space 4} .1626151{col 70}{space 3} 5.144919
{txt}experience_me~n {c |}{col 17}{res}{space 2} .9997547{col 29}{space 2} .0135139{col 40}{space 1}   -0.02{col 49}{space 3}0.986{col 57}{space 4} .9736158{col 70}{space 3} 1.026595
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9912814{col 29}{space 2} .0048231{col 40}{space 1}   -1.80{col 49}{space 3}0.072{col 57}{space 4} .9818733{col 70}{space 3}  1.00078
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8648091{col 29}{space 2} .0883769{col 40}{space 1}   -1.42{col 49}{space 3}0.155{col 57}{space 4} .7078382{col 70}{space 3}  1.05659
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003738{col 29}{space 2} .0025507{col 40}{space 1}    1.47{col 49}{space 3}0.142{col 57}{space 4} .9987515{col 70}{space 3}  1.00875
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.515586{col 29}{space 2} .2255569{col 40}{space 1}   10.29{col 49}{space 3}0.000{col 57}{space 4} 2.110169{col 70}{space 3} 2.998894
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7983014{col 29}{space 2} .0521039{col 40}{space 1}   -3.45{col 49}{space 3}0.001{col 57}{space 4} .7024417{col 70}{space 3} .9072427
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8781204{col 29}{space 2} .0687737{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4} .7531623{col 70}{space 3}  1.02381
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2}  .999947{col 29}{space 2} .0000364{col 40}{space 1}   -1.45{col 49}{space 3}0.146{col 57}{space 4} .9998756{col 70}{space 3} 1.000018
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0456647{col 29}{space 2} .0663995{col 40}{space 1}   -2.12{col 49}{space 3}0.034{col 57}{space 4} .0026417{col 70}{space 3} .7893778
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002445{col 29}{space 2} .0014725{col 40}{space 1}    1.66{col 49}{space 3}0.096{col 57}{space 4} .9995634{col 70}{space 3} 1.005336
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.004798{col 29}{space 2} .0454481{col 40}{space 1}    0.11{col 49}{space 3}0.916{col 57}{space 4} .9195553{col 70}{space 3} 1.097942
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2} .9639302{col 29}{space 2} .0511406{col 40}{space 1}   -0.69{col 49}{space 3}0.489{col 57}{space 4} .8687318{col 70}{space 3} 1.069561
{txt}{space 9}denied {c |}{col 17}{res}{space 2} .6189441{col 29}{space 2} .0600541{col 40}{space 1}   -4.94{col 49}{space 3}0.000{col 57}{space 4} .5117551{col 70}{space 3} .7485842
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9361678{col 29}{space 2} .0531486{col 40}{space 1}   -1.16{col 49}{space 3}0.245{col 57}{space 4} .8375848{col 70}{space 3} 1.046354
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .7541039{col 29}{space 2} .1579325{col 40}{space 1}   -1.35{col 49}{space 3}0.178{col 57}{space 4} .5002228{col 70}{space 3} 1.136839
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .7693182{col 29}{space 2} .0970183{col 40}{space 1}   -2.08{col 49}{space 3}0.038{col 57}{space 4} .6008436{col 70}{space 3} .9850324
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9390745{col 29}{space 2} .0944721{col 40}{space 1}   -0.62{col 49}{space 3}0.532{col 57}{space 4} .7710243{col 70}{space 3} 1.143752
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9342489{col 29}{space 2} .0843714{col 40}{space 1}   -0.75{col 49}{space 3}0.451{col 57}{space 4} .7826924{col 70}{space 3} 1.115152
{txt}{space 9}social {c |}{col 17}{res}{space 2} .8887637{col 29}{space 2} .0778799{col 40}{space 1}   -1.35{col 49}{space 3}0.178{col 57}{space 4} .7485104{col 70}{space 3} 1.055297
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.217041{col 29}{space 2} .0851121{col 40}{space 1}    2.81{col 49}{space 3}0.005{col 57}{space 4} 1.061152{col 70}{space 3} 1.395831
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} 1.021508{col 29}{space 2} .0558869{col 40}{space 1}    0.39{col 49}{space 3}0.697{col 57}{space 4} .9176402{col 70}{space 3} 1.137133
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .8006373{col 29}{space 2} .0773406{col 40}{space 1}   -2.30{col 49}{space 3}0.021{col 57}{space 4} .6625379{col 70}{space 3} .9675221
{txt}policy_majage~y {c |}{col 17}{res}{space 2}  1.30433{col 29}{space 2} .1030858{col 40}{space 1}    3.36{col 49}{space 3}0.001{col 57}{space 4} 1.117156{col 70}{space 3} 1.522863
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.067329{col 29}{space 2} .1654491{col 40}{space 1}    0.42{col 49}{space 3}0.674{col 57}{space 4}  .787683{col 70}{space 3} 1.446255
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .9515319{col 29}{space 2} .0892447{col 40}{space 1}   -0.53{col 49}{space 3}0.596{col 57}{space 4}  .791751{col 70}{space 3} 1.143558
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.659096{col 29}{space 2} .3251622{col 40}{space 1}    8.00{col 49}{space 3}0.000{col 57}{space 4} 2.092409{col 70}{space 3} 3.379259
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.367686{col 29}{space 2} .2675745{col 40}{space 1}    1.60{col 49}{space 3}0.109{col 57}{space 4} .9320888{col 70}{space 3} 2.006854
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.661179{col 29}{space 2} .2884395{col 40}{space 1}    2.92{col 49}{space 3}0.003{col 57}{space 4}    1.182{col 70}{space 3} 2.334614
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.154306{col 29}{space 2} .1341394{col 40}{space 1}    1.23{col 49}{space 3}0.217{col 57}{space 4} .9191888{col 70}{space 3} 1.449564
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.030569{col 29}{space 2} .3250834{col 40}{space 1}    0.10{col 49}{space 3}0.924{col 57}{space 4} .5553589{col 70}{space 3} 1.912409
{txt}{space 13}9  {c |}{col 17}{res}{space 2}  .947359{col 29}{space 2} .1509469{col 40}{space 1}   -0.34{col 49}{space 3}0.734{col 57}{space 4} .6932484{col 70}{space 3} 1.294614
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7719371{col 29}{space 2} .2176892{col 40}{space 1}   -0.92{col 49}{space 3}0.359{col 57}{space 4} .4441603{col 70}{space 3} 1.341603
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.214871{col 29}{space 2} .3431928{col 40}{space 1}    0.69{col 49}{space 3}0.491{col 57}{space 4} .6983477{col 70}{space 3} 2.113435
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.260107{col 29}{space 2} .5071552{col 40}{space 1}    0.57{col 49}{space 3}0.566{col 57}{space 4} .5725644{col 70}{space 3} 2.773259
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .6598796{col 29}{space 2} .0722738{col 40}{space 1}   -3.80{col 49}{space 3}0.000{col 57}{space 4} .5323978{col 70}{space 3} .8178868
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.113895{col 29}{space 2}  .266689{col 40}{space 1}    0.45{col 49}{space 3}0.652{col 57}{space 4} .6967057{col 70}{space 3} 1.780898
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 1.842508{col 29}{space 2} .8266046{col 40}{space 1}    1.36{col 49}{space 3}0.173{col 57}{space 4} .7647771{col 70}{space 3} 4.438989
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.315284{col 29}{space 2} .4677574{col 40}{space 1}    0.77{col 49}{space 3}0.441{col 57}{space 4} .6550957{col 70}{space 3} 2.640792
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5333731{col 29}{space 2} .0961932{col 40}{space 1}   -3.49{col 49}{space 3}0.000{col 57}{space 4}  .374557{col 70}{space 3} .7595289
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .5608382{col 29}{space 2} .1663418{col 40}{space 1}   -1.95{col 49}{space 3}0.051{col 57}{space 4} .3135996{col 70}{space 3} 1.002997
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5254151{col 29}{space 2} .0621632{col 40}{space 1}   -5.44{col 49}{space 3}0.000{col 57}{space 4} .4166724{col 70}{space 3} .6625375
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9202038{col 29}{space 2} .1096887{col 40}{space 1}   -0.70{col 49}{space 3}0.485{col 57}{space 4} .7284847{col 70}{space 3} 1.162379
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.844959{col 29}{space 2} .4352585{col 40}{space 1}    2.60{col 49}{space 3}0.009{col 57}{space 4} 1.161912{col 70}{space 3} 2.929546
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.601476{col 29}{space 2} .5144948{col 40}{space 1}    1.47{col 49}{space 3}0.143{col 57}{space 4} .8532201{col 70}{space 3} 3.005937
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.534592{col 29}{space 2} .4002308{col 40}{space 1}    1.64{col 49}{space 3}0.101{col 57}{space 4} .9204378{col 70}{space 3} 2.558535
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.133633{col 29}{space 2} .4302428{col 40}{space 1}    0.33{col 49}{space 3}0.741{col 57}{space 4}   .53879{col 70}{space 3} 2.385203
{txt}{space 13}6  {c |}{col 17}{res}{space 2} .9335867{col 29}{space 2} .4576818{col 40}{space 1}   -0.14{col 49}{space 3}0.889{col 57}{space 4} .3571588{col 70}{space 3} 2.440327
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .2580003{col 29}{space 2} .2051299{col 40}{space 1}   -1.70{col 49}{space 3}0.088{col 57}{space 4} .0543063{col 70}{space 3} 1.225717
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2}  .050449{col 29}{space 2} .0182583{col 40}{space 1}    2.76{col 49}{space 3}0.006{col 57}{space 4} .0146634{col 70}{space 3} .0862346
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} 1.051743{col 29}{space 2} .0192031{col 57}{space 4} 1.014771{col 70}{space 3} 1.090062
{txt}            1/p {c |}{col 17}{res}{space 2} .9508024{col 29}{space 2}   .01736{col 57}{space 4}  .917379{col 70}{space 3} .9854436
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}     9,879{col 28}-14091.78{col 39}-13067.46{col 50}    19{col 58} 26172.92{col 69} 26309.69
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. estimates store model3
{txt}
{com}. estout model3, cells(b(star fmt(3)) se(par fmt(3))) eform
{res}
{txt}{hline 28}
{txt}                   model3   
{txt}                     b/se   
{txt}{hline 28}
{res}_t                          {txt}
{txt}committee_~1{res}        0.332   {txt}
            {res}      (0.238)   {txt}
{txt}0.sendivide {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivide {res}        0.236*  {txt}
            {res}      (0.135)   {txt}
{txt}0.sendivid~1{res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivid~1{res}        7.103** {txt}
            {res}      (4.738)   {txt}
{txt}pressenflo~t{res}        0.915   {txt}
            {res}      (0.806)   {txt}
{txt}experience~n{res}        1.000   {txt}
            {res}      (0.014)   {txt}
{txt}committees~e{res}        0.991   {txt}
            {res}      (0.005)   {txt}
{txt}ln_combill~d{res}        0.865   {txt}
            {res}      (0.088)   {txt}
{txt}pres_app_m  {res}        1.004   {txt}
            {res}      (0.003)   {txt}
{txt}first90     {res}        2.516***{txt}
            {res}      (0.226)   {txt}
{txt}preselection{res}        0.798***{txt}
            {res}      (0.052)   {txt}
{txt}lameduck    {res}        0.878   {txt}
            {res}      (0.069)   {txt}
{txt}kv_workload {res}        1.000   {txt}
            {res}      (0.000)   {txt}
{txt}polarization{res}        0.046*  {txt}
            {res}      (0.066)   {txt}
{txt}workload    {res}        1.002   {txt}
            {res}      (0.001)   {txt}
{txt}female      {res}        1.005   {txt}
            {res}      (0.045)   {txt}
{txt}priorconfirm{res}        0.964   {txt}
            {res}      (0.051)   {txt}
{txt}denied      {res}        0.619***{txt}
            {res}      (0.060)   {txt}
{txt}x_itier_2   {res}        0.936   {txt}
            {res}      (0.053)   {txt}
{txt}x_itier_3   {res}        0.754   {txt}
            {res}      (0.158)   {txt}
{txt}x_itier_4   {res}        0.769*  {txt}
            {res}      (0.097)   {txt}
{txt}defense     {res}        0.939   {txt}
            {res}      (0.094)   {txt}
{txt}infrastruc~e{res}        0.934   {txt}
            {res}      (0.084)   {txt}
{txt}social      {res}        0.889   {txt}
            {res}      (0.078)   {txt}
{txt}fvra        {res}        1.217** {txt}
            {res}      (0.085)   {txt}
{txt}firstrecess {res}        1.022   {txt}
            {res}      (0.056)   {txt}
{txt}secondrecess{res}        0.801*  {txt}
            {res}      (0.077)   {txt}
{txt}policy_maj~y{res}        1.304***{txt}
            {res}      (0.103)   {txt}
{txt}1.kbcom_1   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.kbcom_1   {res}        1.067   {txt}
            {res}      (0.165)   {txt}
{txt}3.kbcom_1   {res}        0.952   {txt}
            {res}      (0.089)   {txt}
{txt}4.kbcom_1   {res}        2.659***{txt}
            {res}      (0.325)   {txt}
{txt}5.kbcom_1   {res}        1.368   {txt}
            {res}      (0.268)   {txt}
{txt}6.kbcom_1   {res}        1.661** {txt}
            {res}      (0.288)   {txt}
{txt}7.kbcom_1   {res}        1.154   {txt}
            {res}      (0.134)   {txt}
{txt}8.kbcom_1   {res}        1.031   {txt}
            {res}      (0.325)   {txt}
{txt}9.kbcom_1   {res}        0.947   {txt}
            {res}      (0.151)   {txt}
{txt}10.kbcom_1  {res}        0.772   {txt}
            {res}      (0.218)   {txt}
{txt}11.kbcom_1  {res}        1.215   {txt}
            {res}      (0.343)   {txt}
{txt}12.kbcom_1  {res}        1.260   {txt}
            {res}      (0.507)   {txt}
{txt}13.kbcom_1  {res}        0.660***{txt}
            {res}      (0.072)   {txt}
{txt}14.kbcom_1  {res}        1.114   {txt}
            {res}      (0.267)   {txt}
{txt}15.kbcom_1  {res}        1.843   {txt}
            {res}      (0.827)   {txt}
{txt}16.kbcom_1  {res}        1.315   {txt}
            {res}      (0.468)   {txt}
{txt}17.kbcom_1  {res}        0.533***{txt}
            {res}      (0.096)   {txt}
{txt}18.kbcom_1  {res}        0.561   {txt}
            {res}      (0.166)   {txt}
{txt}19.kbcom_1  {res}        0.525***{txt}
            {res}      (0.062)   {txt}
{txt}20.kbcom_1  {res}        0.920   {txt}
            {res}      (0.110)   {txt}
{txt}1.presrev   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.presrev   {res}        1.845** {txt}
            {res}      (0.435)   {txt}
{txt}3.presrev   {res}        1.601   {txt}
            {res}      (0.514)   {txt}
{txt}4.presrev   {res}        1.535   {txt}
            {res}      (0.400)   {txt}
{txt}5.presrev   {res}        1.134   {txt}
            {res}      (0.430)   {txt}
{txt}6.presrev   {res}        0.934   {txt}
            {res}      (0.458)   {txt}
{txt}_cons       {res}        0.258   {txt}
            {res}      (0.205)   {txt}
{txt}{hline 28}
{res}/                           {txt}
{txt}ln_p        {res}        1.052** {txt}
            {res}      (0.019)   {txt}
{txt}{hline 28}

{com}. 
. *
. *
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"  *
. lincomest (committee_pres1 * 0.303 +  1.sendivide#c.committee_pres1 * 0.2483547) - committee_pres1 * 0.303, eform(hr)
{txt}Confidence interval for formula:
{res}(committee_pres1*0.303+1.sendivide#c.committee_pres1*0.2483547)-committee_pres1*0.303

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.627268{col 26}{space 2} .2695581{col 37}{space 1}    2.94{col 46}{space 3}0.003{col 54}{space 4} 1.176134{col 67}{space 3} 2.251444
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model3 = r(table)
{txt}
{com}. mat list model3
{res}
{txt}model3[9,1]
               (1)
     b {res} 1.6272677
{txt}    se {res} .26955812
{txt}     z {res} 2.9393307
{txt}pvalue {res} .00328922
{txt}    ll {res}  1.176134
{txt}    ul {res} 2.2514441
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. *
. *
. *
. 
. **** COMPUTE DIFFERENTIAL MARGINAL MEDIAN SURVIVAL EFFECTS:DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"   *****
. 
. ** Generate 'manual' interaction variable ** 
. generate dpc_committee_pres1 = sendivide*committee_pres1
{txt}(421 missing values generated)

{com}. 
. 
. ** Re-Estimate Model 3  with 'manual' interaction variable **
. streg  committee_pres1 sendivide dpc_committee_pres1   pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency i.kbcom_1 i.presrev, distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-14114.273
{txt}Iteration 1:  Log pseudolikelihood = {res}-14091.777
{txt}Iteration 2:  Log pseudolikelihood = {res}-14091.776

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-14091.776}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-13949.799}  
Iteration 2:{space 2}Log pseudolikelihood = {res: -13092.61}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-13067.546}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-13067.462}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-13067.462}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:9,879}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:9,879}
{txt}No. of failures = {res}{ralign 7:7,076}
{txt}Time at risk    = {res}{ralign 7:987,811}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(17)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-13067.462{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .3322358{col 29}{space 2} .2383764{col 40}{space 1}   -1.54{col 49}{space 3}0.125{col 57}{space 4} .0814172{col 70}{space 3}  1.35574
{txt}{space 6}sendivide {c |}{col 17}{res}{space 2} .2362705{col 29}{space 2} .1349489{col 40}{space 1}   -2.53{col 49}{space 3}0.012{col 57}{space 4} .0771321{col 70}{space 3} .7237425
{txt}dpc_committee~1 {c |}{col 17}{res}{space 2} 7.102962{col 29}{space 2} 4.737623{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} 1.921739{col 70}{space 3} 26.25334
{txt}pressenfloora~t {c |}{col 17}{res}{space 2}  .914681{col 29}{space 2} .8060492{col 40}{space 1}   -0.10{col 49}{space 3}0.919{col 57}{space 4} .1626151{col 70}{space 3} 5.144919
{txt}experience_me~n {c |}{col 17}{res}{space 2} .9997547{col 29}{space 2} .0135139{col 40}{space 1}   -0.02{col 49}{space 3}0.986{col 57}{space 4} .9736158{col 70}{space 3} 1.026595
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9912814{col 29}{space 2} .0048231{col 40}{space 1}   -1.80{col 49}{space 3}0.072{col 57}{space 4} .9818733{col 70}{space 3}  1.00078
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8648091{col 29}{space 2} .0883769{col 40}{space 1}   -1.42{col 49}{space 3}0.155{col 57}{space 4} .7078382{col 70}{space 3}  1.05659
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003738{col 29}{space 2} .0025507{col 40}{space 1}    1.47{col 49}{space 3}0.142{col 57}{space 4} .9987515{col 70}{space 3}  1.00875
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.515586{col 29}{space 2} .2255569{col 40}{space 1}   10.29{col 49}{space 3}0.000{col 57}{space 4} 2.110169{col 70}{space 3} 2.998894
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7983014{col 29}{space 2} .0521039{col 40}{space 1}   -3.45{col 49}{space 3}0.001{col 57}{space 4} .7024417{col 70}{space 3} .9072427
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8781204{col 29}{space 2} .0687737{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4} .7531623{col 70}{space 3}  1.02381
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2}  .999947{col 29}{space 2} .0000364{col 40}{space 1}   -1.45{col 49}{space 3}0.146{col 57}{space 4} .9998756{col 70}{space 3} 1.000018
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0456647{col 29}{space 2} .0663995{col 40}{space 1}   -2.12{col 49}{space 3}0.034{col 57}{space 4} .0026417{col 70}{space 3} .7893778
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002445{col 29}{space 2} .0014725{col 40}{space 1}    1.66{col 49}{space 3}0.096{col 57}{space 4} .9995634{col 70}{space 3} 1.005336
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.004798{col 29}{space 2} .0454481{col 40}{space 1}    0.11{col 49}{space 3}0.916{col 57}{space 4} .9195553{col 70}{space 3} 1.097942
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2} .9639302{col 29}{space 2} .0511406{col 40}{space 1}   -0.69{col 49}{space 3}0.489{col 57}{space 4} .8687318{col 70}{space 3} 1.069561
{txt}{space 9}denied {c |}{col 17}{res}{space 2} .6189441{col 29}{space 2} .0600541{col 40}{space 1}   -4.94{col 49}{space 3}0.000{col 57}{space 4} .5117551{col 70}{space 3} .7485842
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9361678{col 29}{space 2} .0531486{col 40}{space 1}   -1.16{col 49}{space 3}0.245{col 57}{space 4} .8375848{col 70}{space 3} 1.046354
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .7541039{col 29}{space 2} .1579325{col 40}{space 1}   -1.35{col 49}{space 3}0.178{col 57}{space 4} .5002228{col 70}{space 3} 1.136839
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .7693182{col 29}{space 2} .0970183{col 40}{space 1}   -2.08{col 49}{space 3}0.038{col 57}{space 4} .6008436{col 70}{space 3} .9850324
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9390745{col 29}{space 2} .0944721{col 40}{space 1}   -0.62{col 49}{space 3}0.532{col 57}{space 4} .7710243{col 70}{space 3} 1.143752
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9342489{col 29}{space 2} .0843714{col 40}{space 1}   -0.75{col 49}{space 3}0.451{col 57}{space 4} .7826924{col 70}{space 3} 1.115152
{txt}{space 9}social {c |}{col 17}{res}{space 2} .8887637{col 29}{space 2} .0778799{col 40}{space 1}   -1.35{col 49}{space 3}0.178{col 57}{space 4} .7485104{col 70}{space 3} 1.055297
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.217041{col 29}{space 2} .0851121{col 40}{space 1}    2.81{col 49}{space 3}0.005{col 57}{space 4} 1.061152{col 70}{space 3} 1.395831
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} 1.021508{col 29}{space 2} .0558869{col 40}{space 1}    0.39{col 49}{space 3}0.697{col 57}{space 4} .9176402{col 70}{space 3} 1.137133
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .8006373{col 29}{space 2} .0773406{col 40}{space 1}   -2.30{col 49}{space 3}0.021{col 57}{space 4} .6625379{col 70}{space 3} .9675221
{txt}policy_majage~y {c |}{col 17}{res}{space 2}  1.30433{col 29}{space 2} .1030858{col 40}{space 1}    3.36{col 49}{space 3}0.001{col 57}{space 4} 1.117156{col 70}{space 3} 1.522863
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.067329{col 29}{space 2} .1654491{col 40}{space 1}    0.42{col 49}{space 3}0.674{col 57}{space 4}  .787683{col 70}{space 3} 1.446255
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .9515319{col 29}{space 2} .0892447{col 40}{space 1}   -0.53{col 49}{space 3}0.596{col 57}{space 4}  .791751{col 70}{space 3} 1.143558
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.659096{col 29}{space 2} .3251622{col 40}{space 1}    8.00{col 49}{space 3}0.000{col 57}{space 4} 2.092409{col 70}{space 3} 3.379259
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.367686{col 29}{space 2} .2675745{col 40}{space 1}    1.60{col 49}{space 3}0.109{col 57}{space 4} .9320888{col 70}{space 3} 2.006854
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.661179{col 29}{space 2} .2884395{col 40}{space 1}    2.92{col 49}{space 3}0.003{col 57}{space 4}    1.182{col 70}{space 3} 2.334614
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.154306{col 29}{space 2} .1341394{col 40}{space 1}    1.23{col 49}{space 3}0.217{col 57}{space 4} .9191888{col 70}{space 3} 1.449564
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.030569{col 29}{space 2} .3250834{col 40}{space 1}    0.10{col 49}{space 3}0.924{col 57}{space 4} .5553589{col 70}{space 3} 1.912409
{txt}{space 13}9  {c |}{col 17}{res}{space 2}  .947359{col 29}{space 2} .1509469{col 40}{space 1}   -0.34{col 49}{space 3}0.734{col 57}{space 4} .6932484{col 70}{space 3} 1.294614
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7719371{col 29}{space 2} .2176892{col 40}{space 1}   -0.92{col 49}{space 3}0.359{col 57}{space 4} .4441603{col 70}{space 3} 1.341603
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.214871{col 29}{space 2} .3431928{col 40}{space 1}    0.69{col 49}{space 3}0.491{col 57}{space 4} .6983477{col 70}{space 3} 2.113435
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.260107{col 29}{space 2} .5071552{col 40}{space 1}    0.57{col 49}{space 3}0.566{col 57}{space 4} .5725644{col 70}{space 3} 2.773259
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .6598796{col 29}{space 2} .0722738{col 40}{space 1}   -3.80{col 49}{space 3}0.000{col 57}{space 4} .5323978{col 70}{space 3} .8178868
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.113895{col 29}{space 2}  .266689{col 40}{space 1}    0.45{col 49}{space 3}0.652{col 57}{space 4} .6967057{col 70}{space 3} 1.780898
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 1.842508{col 29}{space 2} .8266046{col 40}{space 1}    1.36{col 49}{space 3}0.173{col 57}{space 4} .7647771{col 70}{space 3} 4.438989
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.315284{col 29}{space 2} .4677574{col 40}{space 1}    0.77{col 49}{space 3}0.441{col 57}{space 4} .6550957{col 70}{space 3} 2.640792
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5333731{col 29}{space 2} .0961932{col 40}{space 1}   -3.49{col 49}{space 3}0.000{col 57}{space 4}  .374557{col 70}{space 3} .7595289
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .5608382{col 29}{space 2} .1663418{col 40}{space 1}   -1.95{col 49}{space 3}0.051{col 57}{space 4} .3135996{col 70}{space 3} 1.002997
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5254151{col 29}{space 2} .0621632{col 40}{space 1}   -5.44{col 49}{space 3}0.000{col 57}{space 4} .4166724{col 70}{space 3} .6625375
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9202038{col 29}{space 2} .1096887{col 40}{space 1}   -0.70{col 49}{space 3}0.485{col 57}{space 4} .7284847{col 70}{space 3} 1.162379
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.844959{col 29}{space 2} .4352585{col 40}{space 1}    2.60{col 49}{space 3}0.009{col 57}{space 4} 1.161912{col 70}{space 3} 2.929546
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.601476{col 29}{space 2} .5144948{col 40}{space 1}    1.47{col 49}{space 3}0.143{col 57}{space 4} .8532201{col 70}{space 3} 3.005937
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.534592{col 29}{space 2} .4002308{col 40}{space 1}    1.64{col 49}{space 3}0.101{col 57}{space 4} .9204378{col 70}{space 3} 2.558535
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.133633{col 29}{space 2} .4302428{col 40}{space 1}    0.33{col 49}{space 3}0.741{col 57}{space 4}   .53879{col 70}{space 3} 2.385203
{txt}{space 13}6  {c |}{col 17}{res}{space 2} .9335867{col 29}{space 2} .4576818{col 40}{space 1}   -0.14{col 49}{space 3}0.889{col 57}{space 4} .3571588{col 70}{space 3} 2.440327
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .2580003{col 29}{space 2} .2051299{col 40}{space 1}   -1.70{col 49}{space 3}0.088{col 57}{space 4} .0543063{col 70}{space 3} 1.225717
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2}  .050449{col 29}{space 2} .0182583{col 40}{space 1}    2.76{col 49}{space 3}0.006{col 57}{space 4} .0146634{col 70}{space 3} .0862346
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} 1.051743{col 29}{space 2} .0192031{col 57}{space 4} 1.014771{col 70}{space 3} 1.090062
{txt}            1/p {c |}{col 17}{res}{space 2} .9508024{col 29}{space 2}   .01736{col 57}{space 4}  .917379{col 70}{space 3} .9854436
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. * 
. ** Generate Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on 25th Percentile & 75th Percentile Values of "wSenComm_committee_pres1" under Sendivide==1 (Divided Partisan Control) **
. margins, predict(median time) at(dpc_committee_pres1=(0.0904305 0.3387852))
{res}
{txt}{col 1}Predictive margins{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:9,879}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 16:dpc_committee_~1} = {res:{ralign 8:.0904305}}
{lalign 7:2._at: }{space 0}{lalign 16:dpc_committee_~1} = {res:{ralign 8:.3387852}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 240.1891{col 26}{space 2}  86.9654{col 37}{space 1}    2.76{col 46}{space 3}0.006{col 54}{space 4} 69.74006{col 67}{space 3} 410.6381
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 151.1811{col 26}{space 2} 31.87337{col 37}{space 1}    4.74{col 46}{space 3}0.000{col 54}{space 4} 88.71046{col 67}{space 3} 213.6518
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(dpc_committee_pres1=(0.0904305 0.3387852))  contrast(atcontrast(r))
{res}
{txt}{col 1}Contrasts of predictive margins{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:9,879}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 16:dpc_committee_~1} = {res:{ralign 8:.0904305}}
{lalign 7:2._at: }{space 0}{lalign 16:dpc_committee_~1} = {res:{ralign 8:.3387852}}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     2.60{col 38}{space 2}   0.1066
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-89.00798{col 26}{space 2} 55.15395{col 37}{space 5}-197.1077{col 51}{space 3} 19.09179
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix model3b = r(table)
{txt}
{com}. mat list model3b
{res}
{txt}model3b[9,1]
             r2vs1.
               _at
     b {res} -89.007977
{txt}    se {res}  55.153955
{txt}     z {res} -1.6138095
{txt}pvalue {res}  .10656875
{txt}    ll {res} -197.10774
{txt}    ul {res}  19.091787
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. *
. ** Generate Descriptive Statistics on Committee Confirmation Delay Based on Regression Sample ** 
. sum legvet2 if e(sample) & confirmbinary==1, detail 

                           {txt}legvet2
{hline 61}
      Percentiles      Smallest
 1%    {res}        1              0
{txt} 5%    {res}        9              0
{txt}10%    {res}       15              0       {txt}Obs         {res}      7,076
{txt}25%    {res}       29              0       {txt}Sum of wgt. {res}      7,076

{txt}50%    {res}       57                      {txt}Mean          {res} 72.79706
                        {txt}Largest       Std. dev.     {res} 64.63281
{txt}75%    {res}       93            640
{txt}90%    {res}      145            657       {txt}Variance      {res} 4177.401
{txt}95%    {res}      190            661       {txt}Skewness      {res} 2.534564
{txt}99%    {res}      307            701       {txt}Kurtosis      {res} 14.00793
{txt}
{com}. 
. 
. 
. 
. ** STORE FINAL SET OF RESULTS FOR FIGURES 2 & 3 BELOW ****
. 
. 
. 
. 
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
. 
. 
. * SENATE COMMITTEE CHAIR PREFERENCE DISTANCE & UNIFIED/DIVIDED PARTISAN CONTROL OF SENATE & PRESIDENCY [MODEL 4: WEIBULL PARAMETRIC MODEL] *
. 
. streg   c.chair_pres1##i.sendivide  pressenfloorabsdist  chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck    kv_workload  polarization  workload      female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency  i.kbcom_1 i.presrev,  distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-14114.273
{txt}Iteration 1:  Log pseudolikelihood = {res}-14091.777
{txt}Iteration 2:  Log pseudolikelihood = {res}-14091.776

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-14091.776}  
Iteration 1:{space 2}Log pseudolikelihood = {res: -13937.88}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-13097.357}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-13072.924}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-13072.839}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-13072.839}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:9,879}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:9,879}
{txt}No. of failures = {res}{ralign 7:7,076}
{txt}Time at risk    = {res}{ralign 7:987,811}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(17)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-13072.839{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .8947132{col 29}{space 2} .2758708{col 40}{space 1}   -0.36{col 49}{space 3}0.718{col 57}{space 4} .4889103{col 70}{space 3} 1.637339
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .3803487{col 29}{space 2} .1479851{col 40}{space 1}   -2.48{col 49}{space 3}0.013{col 57}{space 4} .1774184{col 70}{space 3} .8153898
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 2}c.chair_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 2.615428{col 29}{space 2} 1.112965{col 40}{space 1}    2.26{col 49}{space 3}0.024{col 57}{space 4} 1.135857{col 70}{space 3}  6.02229
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} .4229917{col 29}{space 2} .3069534{col 40}{space 1}   -1.19{col 49}{space 3}0.236{col 57}{space 4}  .102009{col 70}{space 3} 1.753983
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.005293{col 29}{space 2}   .00246{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} 1.000483{col 70}{space 3} 1.010126
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9922507{col 29}{space 2} .0052683{col 40}{space 1}   -1.47{col 49}{space 3}0.143{col 57}{space 4} .9819786{col 70}{space 3}  1.00263
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8281649{col 29}{space 2}  .081252{col 40}{space 1}   -1.92{col 49}{space 3}0.055{col 57}{space 4} .6832894{col 70}{space 3} 1.003758
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003305{col 29}{space 2}  .002285{col 40}{space 1}    1.45{col 49}{space 3}0.147{col 57}{space 4} .9988365{col 70}{space 3} 1.007794
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.560396{col 29}{space 2} .1970263{col 40}{space 1}   12.22{col 49}{space 3}0.000{col 57}{space 4} 2.201942{col 70}{space 3} 2.977202
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7889673{col 29}{space 2}  .054805{col 40}{space 1}   -3.41{col 49}{space 3}0.001{col 57}{space 4} .6885428{col 70}{space 3} .9040389
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8601654{col 29}{space 2} .0826583{col 40}{space 1}   -1.57{col 49}{space 3}0.117{col 57}{space 4} .7125004{col 70}{space 3} 1.038434
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999626{col 29}{space 2} .0000385{col 40}{space 1}   -0.97{col 49}{space 3}0.331{col 57}{space 4} .9998871{col 70}{space 3} 1.000038
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0198839{col 29}{space 2} .0304113{col 40}{space 1}   -2.56{col 49}{space 3}0.010{col 57}{space 4} .0009923{col 70}{space 3}   .39844
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002277{col 29}{space 2} .0014809{col 40}{space 1}    1.54{col 49}{space 3}0.124{col 57}{space 4} .9993785{col 70}{space 3} 1.005183
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.003322{col 29}{space 2} .0452139{col 40}{space 1}    0.07{col 49}{space 3}0.941{col 57}{space 4} .9185048{col 70}{space 3} 1.095971
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2} .9527189{col 29}{space 2} .0557574{col 40}{space 1}   -0.83{col 49}{space 3}0.408{col 57}{space 4} .8494712{col 70}{space 3} 1.068516
{txt}{space 9}denied {c |}{col 17}{res}{space 2} .6156968{col 29}{space 2} .0626095{col 40}{space 1}   -4.77{col 49}{space 3}0.000{col 57}{space 4} .5044396{col 70}{space 3} .7514924
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9161344{col 29}{space 2} .0570083{col 40}{space 1}   -1.41{col 49}{space 3}0.159{col 57}{space 4} .8109452{col 70}{space 3} 1.034968
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .7420245{col 29}{space 2} .1522025{col 40}{space 1}   -1.45{col 49}{space 3}0.146{col 57}{space 4} .4963884{col 70}{space 3} 1.109213
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .7680634{col 29}{space 2} .0986021{col 40}{space 1}   -2.06{col 49}{space 3}0.040{col 57}{space 4}  .597203{col 70}{space 3} .9878072
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9524728{col 29}{space 2} .0866274{col 40}{space 1}   -0.54{col 49}{space 3}0.592{col 57}{space 4} .7969587{col 70}{space 3} 1.138333
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9332087{col 29}{space 2} .0773385{col 40}{space 1}   -0.83{col 49}{space 3}0.404{col 57}{space 4} .7932983{col 70}{space 3} 1.097795
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9064267{col 29}{space 2} .0852197{col 40}{space 1}   -1.04{col 49}{space 3}0.296{col 57}{space 4}  .753885{col 70}{space 3} 1.089834
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.219858{col 29}{space 2} .0880689{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} 1.058902{col 70}{space 3} 1.405279
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} 1.020234{col 29}{space 2} .0561303{col 40}{space 1}    0.36{col 49}{space 3}0.716{col 57}{space 4} .9159442{col 70}{space 3} 1.136398
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .8132311{col 29}{space 2} .0763609{col 40}{space 1}   -2.20{col 49}{space 3}0.028{col 57}{space 4}  .676531{col 70}{space 3} .9775529
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.327481{col 29}{space 2} .1095547{col 40}{space 1}    3.43{col 49}{space 3}0.001{col 57}{space 4} 1.129224{col 70}{space 3} 1.560546
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .9606624{col 29}{space 2}  .112196{col 40}{space 1}   -0.34{col 49}{space 3}0.731{col 57}{space 4}  .764115{col 70}{space 3} 1.207766
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .9571822{col 29}{space 2} .0692116{col 40}{space 1}   -0.61{col 49}{space 3}0.545{col 57}{space 4} .8307039{col 70}{space 3} 1.102917
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.579449{col 29}{space 2}   .35477{col 40}{space 1}    6.89{col 49}{space 3}0.000{col 57}{space 4}  1.96995{col 70}{space 3} 3.377526
{txt}{space 13}5  {c |}{col 17}{res}{space 2}  1.32424{col 29}{space 2} .2485773{col 40}{space 1}    1.50{col 49}{space 3}0.135{col 57}{space 4} .9166108{col 70}{space 3} 1.913148
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.707164{col 29}{space 2} .2591743{col 40}{space 1}    3.52{col 49}{space 3}0.000{col 57}{space 4} 1.267796{col 70}{space 3} 2.298799
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.213742{col 29}{space 2} .1319394{col 40}{space 1}    1.78{col 49}{space 3}0.075{col 57}{space 4} .9808365{col 70}{space 3} 1.501951
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.090091{col 29}{space 2} .3439456{col 40}{space 1}    0.27{col 49}{space 3}0.785{col 57}{space 4} .5873423{col 70}{space 3} 2.023177
{txt}{space 13}9  {c |}{col 17}{res}{space 2}   .92915{col 29}{space 2} .1328129{col 40}{space 1}   -0.51{col 49}{space 3}0.607{col 57}{space 4} .7021258{col 70}{space 3}  1.22958
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7667847{col 29}{space 2} .2288735{col 40}{space 1}   -0.89{col 49}{space 3}0.374{col 57}{space 4}  .427172{col 70}{space 3} 1.376398
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.314199{col 29}{space 2} .4045594{col 40}{space 1}    0.89{col 49}{space 3}0.375{col 57}{space 4} .7188353{col 70}{space 3} 2.402662
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.285766{col 29}{space 2} .5511958{col 40}{space 1}    0.59{col 49}{space 3}0.558{col 57}{space 4} .5549576{col 70}{space 3} 2.978956
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .7395716{col 29}{space 2} .0854621{col 40}{space 1}   -2.61{col 49}{space 3}0.009{col 57}{space 4}  .589683{col 70}{space 3} .9275597
{txt}{space 12}14  {c |}{col 17}{res}{space 2} .9766238{col 29}{space 2} .2191881{col 40}{space 1}   -0.11{col 49}{space 3}0.916{col 57}{space 4} .6290545{col 70}{space 3} 1.516234
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 1.783979{col 29}{space 2} .8362019{col 40}{space 1}    1.23{col 49}{space 3}0.217{col 57}{space 4} .7118806{col 70}{space 3} 4.470666
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.352239{col 29}{space 2} .4996328{col 40}{space 1}    0.82{col 49}{space 3}0.414{col 57}{space 4} .6554605{col 70}{space 3} 2.789717
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5615578{col 29}{space 2} .1068755{col 40}{space 1}   -3.03{col 49}{space 3}0.002{col 57}{space 4} .3867177{col 70}{space 3} .8154454
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .5117002{col 29}{space 2} .1470144{col 40}{space 1}   -2.33{col 49}{space 3}0.020{col 57}{space 4} .2913805{col 70}{space 3} .8986089
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5301991{col 29}{space 2} .0601115{col 40}{space 1}   -5.60{col 49}{space 3}0.000{col 57}{space 4} .4245549{col 70}{space 3} .6621314
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9486842{col 29}{space 2} .1212524{col 40}{space 1}   -0.41{col 49}{space 3}0.680{col 57}{space 4} .7384629{col 70}{space 3}  1.21875
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.754888{col 29}{space 2} .3993903{col 40}{space 1}    2.47{col 49}{space 3}0.013{col 57}{space 4}  1.12338{col 70}{space 3} 2.741398
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.468606{col 29}{space 2} .4820043{col 40}{space 1}    1.17{col 49}{space 3}0.242{col 57}{space 4} .7718563{col 70}{space 3} 2.794308
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.526475{col 29}{space 2} .4900565{col 40}{space 1}    1.32{col 49}{space 3}0.188{col 57}{space 4} .8136201{col 70}{space 3}   2.8639
{txt}{space 13}5  {c |}{col 17}{res}{space 2}  1.24676{col 29}{space 2}  .521464{col 40}{space 1}    0.53{col 49}{space 3}0.598{col 57}{space 4} .5492418{col 70}{space 3} 2.830104
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.251875{col 29}{space 2} .5456201{col 40}{space 1}    0.52{col 49}{space 3}0.606{col 57}{space 4}  .532809{col 70}{space 3} 2.941377
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .4584011{col 29}{space 2} .4165308{col 40}{space 1}   -0.86{col 49}{space 3}0.391{col 57}{space 4} .0772312{col 70}{space 3} 2.720812
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2} .0503182{col 29}{space 2} .0156241{col 40}{space 1}    3.22{col 49}{space 3}0.001{col 57}{space 4} .0196956{col 70}{space 3} .0809408
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} 1.051606{col 29}{space 2} .0164304{col 57}{space 4} 1.019891{col 70}{space 3} 1.084307
{txt}            1/p {c |}{col 17}{res}{space 2} .9509268{col 29}{space 2} .0148573{col 57}{space 4} .9222483{col 70}{space 3} .9804971
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}     9,879{col 28}-14091.78{col 39}-13072.84{col 50}    19{col 58} 26183.68{col 69} 26320.44
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. *
. estimates store model4
{txt}
{com}. estout model4, cells(b(star fmt(3)) se(par fmt(3))) eform
{res}
{txt}{hline 28}
{txt}                   model4   
{txt}                     b/se   
{txt}{hline 28}
{res}_t                          {txt}
{txt}chair_pres1 {res}        0.895   {txt}
            {res}      (0.276)   {txt}
{txt}0.sendivide {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivide {res}        0.380*  {txt}
            {res}      (0.148)   {txt}
{txt}0.sendivid~1{res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}1.sendivid~1{res}        2.615*  {txt}
            {res}      (1.113)   {txt}
{txt}pressenflo~t{res}        0.423   {txt}
            {res}      (0.307)   {txt}
{txt}chair_expe~1{res}        1.005*  {txt}
            {res}      (0.002)   {txt}
{txt}committees~e{res}        0.992   {txt}
            {res}      (0.005)   {txt}
{txt}ln_combill~d{res}        0.828   {txt}
            {res}      (0.081)   {txt}
{txt}pres_app_m  {res}        1.003   {txt}
            {res}      (0.002)   {txt}
{txt}first90     {res}        2.560***{txt}
            {res}      (0.197)   {txt}
{txt}preselection{res}        0.789***{txt}
            {res}      (0.055)   {txt}
{txt}lameduck    {res}        0.860   {txt}
            {res}      (0.083)   {txt}
{txt}kv_workload {res}        1.000   {txt}
            {res}      (0.000)   {txt}
{txt}polarization{res}        0.020*  {txt}
            {res}      (0.030)   {txt}
{txt}workload    {res}        1.002   {txt}
            {res}      (0.001)   {txt}
{txt}female      {res}        1.003   {txt}
            {res}      (0.045)   {txt}
{txt}priorconfirm{res}        0.953   {txt}
            {res}      (0.056)   {txt}
{txt}denied      {res}        0.616***{txt}
            {res}      (0.063)   {txt}
{txt}x_itier_2   {res}        0.916   {txt}
            {res}      (0.057)   {txt}
{txt}x_itier_3   {res}        0.742   {txt}
            {res}      (0.152)   {txt}
{txt}x_itier_4   {res}        0.768*  {txt}
            {res}      (0.099)   {txt}
{txt}defense     {res}        0.952   {txt}
            {res}      (0.087)   {txt}
{txt}infrastruc~e{res}        0.933   {txt}
            {res}      (0.077)   {txt}
{txt}social      {res}        0.906   {txt}
            {res}      (0.085)   {txt}
{txt}fvra        {res}        1.220** {txt}
            {res}      (0.088)   {txt}
{txt}firstrecess {res}        1.020   {txt}
            {res}      (0.056)   {txt}
{txt}secondrecess{res}        0.813*  {txt}
            {res}      (0.076)   {txt}
{txt}policy_maj~y{res}        1.327***{txt}
            {res}      (0.110)   {txt}
{txt}1.kbcom_1   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.kbcom_1   {res}        0.961   {txt}
            {res}      (0.112)   {txt}
{txt}3.kbcom_1   {res}        0.957   {txt}
            {res}      (0.069)   {txt}
{txt}4.kbcom_1   {res}        2.579***{txt}
            {res}      (0.355)   {txt}
{txt}5.kbcom_1   {res}        1.324   {txt}
            {res}      (0.249)   {txt}
{txt}6.kbcom_1   {res}        1.707***{txt}
            {res}      (0.259)   {txt}
{txt}7.kbcom_1   {res}        1.214   {txt}
            {res}      (0.132)   {txt}
{txt}8.kbcom_1   {res}        1.090   {txt}
            {res}      (0.344)   {txt}
{txt}9.kbcom_1   {res}        0.929   {txt}
            {res}      (0.133)   {txt}
{txt}10.kbcom_1  {res}        0.767   {txt}
            {res}      (0.229)   {txt}
{txt}11.kbcom_1  {res}        1.314   {txt}
            {res}      (0.405)   {txt}
{txt}12.kbcom_1  {res}        1.286   {txt}
            {res}      (0.551)   {txt}
{txt}13.kbcom_1  {res}        0.740** {txt}
            {res}      (0.085)   {txt}
{txt}14.kbcom_1  {res}        0.977   {txt}
            {res}      (0.219)   {txt}
{txt}15.kbcom_1  {res}        1.784   {txt}
            {res}      (0.836)   {txt}
{txt}16.kbcom_1  {res}        1.352   {txt}
            {res}      (0.500)   {txt}
{txt}17.kbcom_1  {res}        0.562** {txt}
            {res}      (0.107)   {txt}
{txt}18.kbcom_1  {res}        0.512*  {txt}
            {res}      (0.147)   {txt}
{txt}19.kbcom_1  {res}        0.530***{txt}
            {res}      (0.060)   {txt}
{txt}20.kbcom_1  {res}        0.949   {txt}
            {res}      (0.121)   {txt}
{txt}1.presrev   {res}        1.000   {txt}
            {res}          (.)   {txt}
{txt}2.presrev   {res}        1.755*  {txt}
            {res}      (0.399)   {txt}
{txt}3.presrev   {res}        1.469   {txt}
            {res}      (0.482)   {txt}
{txt}4.presrev   {res}        1.526   {txt}
            {res}      (0.490)   {txt}
{txt}5.presrev   {res}        1.247   {txt}
            {res}      (0.521)   {txt}
{txt}6.presrev   {res}        1.252   {txt}
            {res}      (0.546)   {txt}
{txt}_cons       {res}        0.458   {txt}
            {res}      (0.417)   {txt}
{txt}{hline 28}
{res}/                           {txt}
{txt}ln_p        {res}        1.052** {txt}
            {res}      (0.016)   {txt}
{txt}{hline 28}

{com}. *
. *
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1" *
. lincomest (chair_pres1 * 0.2724212 +  1.sendivide#c.chair_pres1 * 0.2364347) - chair_pres1 * 0.2724212, eform(hr)
{txt}Confidence interval for formula:
{res}(chair_pres1*0.2724212+1.sendivide#c.chair_pres1*0.2364347)-chair_pres1*0.2724212

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.255225{col 26}{space 2} .1262908{col 37}{space 1}    2.26{col 46}{space 3}0.024{col 54}{space 4} 1.030577{col 67}{space 3} 1.528842
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model4 = r(table)
{txt}
{com}. mat list model4
{res}
{txt}model4[9,1]
               (1)
     b {res}  1.255225
{txt}    se {res} .12629075
{txt}     z {res} 2.2593204
{txt}pvalue {res} .02386346
{txt}    ll {res}  1.030577
{txt}    ul {res} 1.5288424
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. *
. *
. *
. *
. *
. 
. **** COMPUTE DIFFERENTIAL MARGINAL MEDIAN SURVIVAL EFFECTS:DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1"   *****
. 
. ** Generate 'manual' interaction variable ** 
. generate dpc_chair_pres1 = sendivide*chair_pres1
{txt}(421 missing values generated)

{com}. 
. ** Re-Estimate Model 4  with 'manual' interaction variable **
. streg   chair_pres1 sendivide dpc_chair_pres1  pressenfloorabsdist  chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck    kv_workload  polarization  workload female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency  i.kbcom_1 i.presrev, distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-14114.273
{txt}Iteration 1:  Log pseudolikelihood = {res}-14091.777
{txt}Iteration 2:  Log pseudolikelihood = {res}-14091.776

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-14091.776}  
Iteration 1:{space 2}Log pseudolikelihood = {res: -13937.88}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-13097.357}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-13072.924}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-13072.839}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-13072.839}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:9,879}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:9,879}
{txt}No. of failures = {res}{ralign 7:7,076}
{txt}Time at risk    = {res}{ralign 7:987,811}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(17)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-13072.839{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .8947132{col 29}{space 2} .2758708{col 40}{space 1}   -0.36{col 49}{space 3}0.718{col 57}{space 4} .4889103{col 70}{space 3} 1.637339
{txt}{space 6}sendivide {c |}{col 17}{res}{space 2} .3803487{col 29}{space 2} .1479851{col 40}{space 1}   -2.48{col 49}{space 3}0.013{col 57}{space 4} .1774184{col 70}{space 3} .8153898
{txt}dpc_chair_pres1 {c |}{col 17}{res}{space 2} 2.615428{col 29}{space 2} 1.112965{col 40}{space 1}    2.26{col 49}{space 3}0.024{col 57}{space 4} 1.135857{col 70}{space 3}  6.02229
{txt}pressenfloora~t {c |}{col 17}{res}{space 2} .4229917{col 29}{space 2} .3069534{col 40}{space 1}   -1.19{col 49}{space 3}0.236{col 57}{space 4}  .102009{col 70}{space 3} 1.753983
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.005293{col 29}{space 2}   .00246{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} 1.000483{col 70}{space 3} 1.010126
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9922507{col 29}{space 2} .0052683{col 40}{space 1}   -1.47{col 49}{space 3}0.143{col 57}{space 4} .9819786{col 70}{space 3}  1.00263
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8281649{col 29}{space 2}  .081252{col 40}{space 1}   -1.92{col 49}{space 3}0.055{col 57}{space 4} .6832894{col 70}{space 3} 1.003758
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003305{col 29}{space 2}  .002285{col 40}{space 1}    1.45{col 49}{space 3}0.147{col 57}{space 4} .9988365{col 70}{space 3} 1.007794
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.560396{col 29}{space 2} .1970263{col 40}{space 1}   12.22{col 49}{space 3}0.000{col 57}{space 4} 2.201942{col 70}{space 3} 2.977202
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7889673{col 29}{space 2}  .054805{col 40}{space 1}   -3.41{col 49}{space 3}0.001{col 57}{space 4} .6885428{col 70}{space 3} .9040389
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8601654{col 29}{space 2} .0826583{col 40}{space 1}   -1.57{col 49}{space 3}0.117{col 57}{space 4} .7125004{col 70}{space 3} 1.038434
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999626{col 29}{space 2} .0000385{col 40}{space 1}   -0.97{col 49}{space 3}0.331{col 57}{space 4} .9998871{col 70}{space 3} 1.000038
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0198839{col 29}{space 2} .0304113{col 40}{space 1}   -2.56{col 49}{space 3}0.010{col 57}{space 4} .0009923{col 70}{space 3}   .39844
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002277{col 29}{space 2} .0014809{col 40}{space 1}    1.54{col 49}{space 3}0.124{col 57}{space 4} .9993785{col 70}{space 3} 1.005183
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.003322{col 29}{space 2} .0452139{col 40}{space 1}    0.07{col 49}{space 3}0.941{col 57}{space 4} .9185048{col 70}{space 3} 1.095971
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2} .9527189{col 29}{space 2} .0557574{col 40}{space 1}   -0.83{col 49}{space 3}0.408{col 57}{space 4} .8494712{col 70}{space 3} 1.068516
{txt}{space 9}denied {c |}{col 17}{res}{space 2} .6156968{col 29}{space 2} .0626095{col 40}{space 1}   -4.77{col 49}{space 3}0.000{col 57}{space 4} .5044396{col 70}{space 3} .7514924
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9161344{col 29}{space 2} .0570083{col 40}{space 1}   -1.41{col 49}{space 3}0.159{col 57}{space 4} .8109452{col 70}{space 3} 1.034968
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .7420245{col 29}{space 2} .1522025{col 40}{space 1}   -1.45{col 49}{space 3}0.146{col 57}{space 4} .4963884{col 70}{space 3} 1.109213
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .7680634{col 29}{space 2} .0986021{col 40}{space 1}   -2.06{col 49}{space 3}0.040{col 57}{space 4}  .597203{col 70}{space 3} .9878072
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9524728{col 29}{space 2} .0866274{col 40}{space 1}   -0.54{col 49}{space 3}0.592{col 57}{space 4} .7969587{col 70}{space 3} 1.138333
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9332087{col 29}{space 2} .0773385{col 40}{space 1}   -0.83{col 49}{space 3}0.404{col 57}{space 4} .7932983{col 70}{space 3} 1.097795
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9064267{col 29}{space 2} .0852197{col 40}{space 1}   -1.04{col 49}{space 3}0.296{col 57}{space 4}  .753885{col 70}{space 3} 1.089834
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.219858{col 29}{space 2} .0880689{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} 1.058902{col 70}{space 3} 1.405279
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} 1.020234{col 29}{space 2} .0561303{col 40}{space 1}    0.36{col 49}{space 3}0.716{col 57}{space 4} .9159442{col 70}{space 3} 1.136398
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .8132311{col 29}{space 2} .0763609{col 40}{space 1}   -2.20{col 49}{space 3}0.028{col 57}{space 4}  .676531{col 70}{space 3} .9775529
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.327481{col 29}{space 2} .1095547{col 40}{space 1}    3.43{col 49}{space 3}0.001{col 57}{space 4} 1.129224{col 70}{space 3} 1.560546
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .9606624{col 29}{space 2}  .112196{col 40}{space 1}   -0.34{col 49}{space 3}0.731{col 57}{space 4}  .764115{col 70}{space 3} 1.207766
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .9571822{col 29}{space 2} .0692116{col 40}{space 1}   -0.61{col 49}{space 3}0.545{col 57}{space 4} .8307039{col 70}{space 3} 1.102917
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.579449{col 29}{space 2}   .35477{col 40}{space 1}    6.89{col 49}{space 3}0.000{col 57}{space 4}  1.96995{col 70}{space 3} 3.377526
{txt}{space 13}5  {c |}{col 17}{res}{space 2}  1.32424{col 29}{space 2} .2485773{col 40}{space 1}    1.50{col 49}{space 3}0.135{col 57}{space 4} .9166108{col 70}{space 3} 1.913148
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.707164{col 29}{space 2} .2591743{col 40}{space 1}    3.52{col 49}{space 3}0.000{col 57}{space 4} 1.267796{col 70}{space 3} 2.298799
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.213742{col 29}{space 2} .1319394{col 40}{space 1}    1.78{col 49}{space 3}0.075{col 57}{space 4} .9808365{col 70}{space 3} 1.501951
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.090091{col 29}{space 2} .3439456{col 40}{space 1}    0.27{col 49}{space 3}0.785{col 57}{space 4} .5873423{col 70}{space 3} 2.023177
{txt}{space 13}9  {c |}{col 17}{res}{space 2}   .92915{col 29}{space 2} .1328129{col 40}{space 1}   -0.51{col 49}{space 3}0.607{col 57}{space 4} .7021258{col 70}{space 3}  1.22958
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7667847{col 29}{space 2} .2288735{col 40}{space 1}   -0.89{col 49}{space 3}0.374{col 57}{space 4}  .427172{col 70}{space 3} 1.376398
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.314199{col 29}{space 2} .4045594{col 40}{space 1}    0.89{col 49}{space 3}0.375{col 57}{space 4} .7188353{col 70}{space 3} 2.402662
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.285766{col 29}{space 2} .5511958{col 40}{space 1}    0.59{col 49}{space 3}0.558{col 57}{space 4} .5549576{col 70}{space 3} 2.978956
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .7395716{col 29}{space 2} .0854621{col 40}{space 1}   -2.61{col 49}{space 3}0.009{col 57}{space 4}  .589683{col 70}{space 3} .9275597
{txt}{space 12}14  {c |}{col 17}{res}{space 2} .9766238{col 29}{space 2} .2191881{col 40}{space 1}   -0.11{col 49}{space 3}0.916{col 57}{space 4} .6290545{col 70}{space 3} 1.516234
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 1.783979{col 29}{space 2} .8362019{col 40}{space 1}    1.23{col 49}{space 3}0.217{col 57}{space 4} .7118806{col 70}{space 3} 4.470666
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.352239{col 29}{space 2} .4996328{col 40}{space 1}    0.82{col 49}{space 3}0.414{col 57}{space 4} .6554605{col 70}{space 3} 2.789717
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5615578{col 29}{space 2} .1068755{col 40}{space 1}   -3.03{col 49}{space 3}0.002{col 57}{space 4} .3867177{col 70}{space 3} .8154454
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .5117002{col 29}{space 2} .1470144{col 40}{space 1}   -2.33{col 49}{space 3}0.020{col 57}{space 4} .2913805{col 70}{space 3} .8986089
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5301991{col 29}{space 2} .0601115{col 40}{space 1}   -5.60{col 49}{space 3}0.000{col 57}{space 4} .4245549{col 70}{space 3} .6621314
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9486842{col 29}{space 2} .1212524{col 40}{space 1}   -0.41{col 49}{space 3}0.680{col 57}{space 4} .7384629{col 70}{space 3}  1.21875
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.754888{col 29}{space 2} .3993903{col 40}{space 1}    2.47{col 49}{space 3}0.013{col 57}{space 4}  1.12338{col 70}{space 3} 2.741398
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.468606{col 29}{space 2} .4820043{col 40}{space 1}    1.17{col 49}{space 3}0.242{col 57}{space 4} .7718563{col 70}{space 3} 2.794308
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.526475{col 29}{space 2} .4900565{col 40}{space 1}    1.32{col 49}{space 3}0.188{col 57}{space 4} .8136201{col 70}{space 3}   2.8639
{txt}{space 13}5  {c |}{col 17}{res}{space 2}  1.24676{col 29}{space 2}  .521464{col 40}{space 1}    0.53{col 49}{space 3}0.598{col 57}{space 4} .5492418{col 70}{space 3} 2.830104
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.251875{col 29}{space 2} .5456201{col 40}{space 1}    0.52{col 49}{space 3}0.606{col 57}{space 4}  .532809{col 70}{space 3} 2.941377
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .4584011{col 29}{space 2} .4165308{col 40}{space 1}   -0.86{col 49}{space 3}0.391{col 57}{space 4} .0772312{col 70}{space 3} 2.720812
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2} .0503182{col 29}{space 2} .0156241{col 40}{space 1}    3.22{col 49}{space 3}0.001{col 57}{space 4} .0196956{col 70}{space 3} .0809408
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} 1.051606{col 29}{space 2} .0164304{col 57}{space 4} 1.019891{col 70}{space 3} 1.084307
{txt}            1/p {c |}{col 17}{res}{space 2} .9509268{col 29}{space 2} .0148573{col 57}{space 4} .9222483{col 70}{space 3} .9804971
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. * 
. ** Generate Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on 25th Percentile & 75th Percentile Values of "wSenComm_chair_pres1" under Sendivide==1 (Divided Partisan Control) **
. margins, predict(median time) at(dpc_chair_pres1=(0.2528486 0.4892833))
{res}
{txt}{col 1}Predictive margins{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:9,879}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 15:dpc_chair_pres1} = {res:{ralign 8:.2528486}}
{lalign 7:2._at: }{space 0}{lalign 15:dpc_chair_pres1} = {res:{ralign 8:.4892833}}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 144.6763{col 26}{space 2} 26.13551{col 37}{space 1}    5.54{col 46}{space 3}0.000{col 54}{space 4} 93.45169{col 67}{space 3}  195.901
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 116.5522{col 26}{space 2} 10.24234{col 37}{space 1}   11.38{col 46}{space 3}0.000{col 54}{space 4} 96.47761{col 67}{space 3} 136.6268
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(dpc_chair_pres1=(0.2528486 0.4892833))  contrast(atcontrast(r))
{res}
{txt}{col 1}Contrasts of predictive margins{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:9,879}
{txt}{col 1}Model VCE: {res:Robust}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}
{lalign 7:1._at: }{space 0}{lalign 15:dpc_chair_pres1} = {res:{ralign 8:.2528486}}
{lalign 7:2._at: }{space 0}{lalign 15:dpc_chair_pres1} = {res:{ralign 8:.4892833}}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     3.08{col 38}{space 2}   0.0792
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   std. err.{col 38}     [95% con{col 51}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-28.12413{col 26}{space 2} 16.02114{col 37}{space 5}-59.52499{col 51}{space 3} 3.276733
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix model4b = r(table)
{txt}
{com}. mat list model4b
{res}
{txt}model4b[9,1]
             r2vs1.
               _at
     b {res}  -28.12413
{txt}    se {res}  16.021143
{txt}     z {res} -1.7554385
{txt}pvalue {res}  .07918434
{txt}    ll {res} -59.524993
{txt}    ul {res}  3.2767327
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. *
. ** Generate Descriptive Statistics on Committee Confirmation Delay Based on Regression Sample ** 
. sum legvet2 if e(sample) & confirmbinary==1, detail 

                           {txt}legvet2
{hline 61}
      Percentiles      Smallest
 1%    {res}        1              0
{txt} 5%    {res}        9              0
{txt}10%    {res}       15              0       {txt}Obs         {res}      7,076
{txt}25%    {res}       29              0       {txt}Sum of wgt. {res}      7,076

{txt}50%    {res}       57                      {txt}Mean          {res} 72.79706
                        {txt}Largest       Std. dev.     {res} 64.63281
{txt}75%    {res}       93            640
{txt}90%    {res}      145            657       {txt}Variance      {res} 4177.401
{txt}95%    {res}      190            661       {txt}Skewness      {res} 2.534564
{txt}99%    {res}      307            701       {txt}Kurtosis      {res} 14.00793
{txt}
{com}. 
. 
. 
. 
. ** STORE FINAL SET OF RESULTS FOR FIGURES 4 & 5 BELOW ****
. 
. 
. 
. 
. 
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. 
. **** FIGURE 4 ****
. 
. matrix A = J(4, 3, .)
{txt}
{com}. matrix coln A = Point ll95 ul95
{txt}
{com}. matrix rown A = 1 2 3 4
{txt}
{com}. 
. matrix A[1,1] = model1[1,1]
{txt}
{com}. matrix A[1,2] = model1[5,1]
{txt}
{com}. matrix A[1,3] = model1[6,1]
{txt}
{com}. 
. matrix A[2,1] = model2[1,1]
{txt}
{com}. matrix A[2,2] = model2[5,1]
{txt}
{com}. matrix A[2,3] = model2[6,1]
{txt}
{com}. 
. matrix A[3,1] = model3[1,1]
{txt}
{com}. matrix A[3,2] = model3[5,1]
{txt}
{com}. matrix A[3,3] = model3[6,1]
{txt}
{com}. 
. matrix A[4,1] = model4[1,1]
{txt}
{com}. matrix A[4,2] = model4[5,1]
{txt}
{com}. matrix A[4,3] = model4[6,1]
{txt}
{com}. 
. 
. **********
. 
. coefplot (matrix(A[,1]), ci((2 3))), grid(none) xline(1, lcolor(red%40) lpattern(dash)) xtitle("Hazard Ratio", size(small) margin(t=2)) ylabel(1 "Model 1" 2 "Model 2" 3 "Model 3" 4 "Model 4", labsize(small) noticks) mlabel format(%9.3f) mlabposition(12) mlabsize(vsmall) xlabel(0(1)2, angle(0) labsize(small) format(%9.1f)) msymbol(o) mcolor(black) msize(small) title("FIGURE 4:", size(med)) ciopts(lcolor(black)) legend(off) subtitle("Differential Partisan Control Effects of Committee-President Ideological Distance", size(small))
{res}{p 0 4 2}
{txt}(note:  named style
med not found in class
gsize,  default attributes used)
{p_end}
{res}{txt}
{com}. 
. 
. *graph save "Graph" "C:\Users\gk57526\Dropbox\Confirmation Dynamics Project (Jason Byers)\Confirmation Delay & Senate Committees\2023 Version\Fall 2024\Statistics\Graphics\figure2.gph", replace
. 
. graph save "Graph" "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure4.gph", replace
{res}{txt}file {bf:/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure4.gph} saved

{com}. 
. 
. 
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. 
. **** Figure 5 ****
. 
. matrix C = J(2, 3, .)
{txt}
{com}. matrix coln C = Point ll95 ul95
{txt}
{com}. matrix rown C = 1 2
{txt}
{com}. 
. matrix C[1,1] = model3b[1,1]
{txt}
{com}. matrix C[1,2] = model3b[5,1]
{txt}
{com}. matrix C[1,3] = model3b[6,1]
{txt}
{com}. 
. matrix C[2,1] = model4b[1,1]
{txt}
{com}. matrix C[2,2] = model4b[5,1]
{txt}
{com}. matrix C[2,3] = model4b[6,1]
{txt}
{com}. 
. 
. **********
. 
. coefplot (matrix(C[,1]), ci((2 3))), grid(none) xline(0, lcolor(red%40) lpattern(dash)) xtitle("Number of Days", size(small) margin(t=2)) ylabel(1 "Model 3" 2 "Model 4", labsize(small) noticks) mlabel format(%9.0f)  mlabposition(12) mlabsize(vsmall) xlabel(-200(50)50, angle(0) labsize(small)) msymbol(o) mcolor(black) msize(small) title("FIGURE 5:", size(med)) ciopts(lcolor(black)) legend(off) subtitle("Differential Partisan Control Effects" "(Predicted Marginal Median Survival Day Differences)", size(small))
{res}{p 0 4 2}
{txt}(note:  named style
med not found in class
gsize,  default attributes used)
{p_end}
{res}{txt}
{com}. 
. *graph save "Graph" "C:\Users\gk57526\Dropbox\Confirmation Dynamics Project (Jason Byers)\Confirmation Delay & Senate Committees\2023 Version\Fall 2024\Statistics\Graphics\figure5.gph", replace
. 
. graph save "Graph" "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure5.gph", replace
{res}{txt}file {bf:/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Manuscript/Figure5.gph} saved

{com}. 
. 
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. ****************************************************************************************************************************************************************************************
. 
. 
. 
.   
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Output/Committee Delay.MANUSCRIPT RESULTS.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}29 Dec 2024, 23:16:01
{txt}{.-}
{smcl}
{txt}{sf}{ul off}